JP2009006466A - Leg wheel type robot - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a leg-wheel type robot capable of detecting an obstacle without receiving interference from a leg and realizing high adaptability to an unknown step.
A leg-wheel type robot includes a base body 10, leg portions 12 connected to the base body 10 with a degree of freedom, drive wheels 20 rotatably provided on the leg portions 12, and leg portions. A joint motor 40 for applying power to drive the motor 12 and an in-plane scanning leg tip rotatably provided on the leg 12 so that the angle formed by the measuring direction with respect to the extending direction of the leg 12 changes. A sensor 38 and a motor 82 for rotating the in-plane scanning leg tip sensor 38 are provided, and an obstacle is recognized based on measurement results measured at different rotation angles by the in-plane scanning leg tip sensor 38, and based on the recognition result. Then, drive control of the joint motor 40 is performed.
[Selection] Figure 5

Description

  The present invention relates to a leg-wheel type robot that can move over a step, and in particular, can detect an obstacle without receiving interference from a leg, and can realize high adaptability to an unknown step. The present invention relates to a leg wheel type robot that can be used.

  The moving mechanism of the robot is classified into a wheel type, a crawler type, a leg type, or a combination thereof. In general, a wheel type robot has a problem of high mobility on a flat ground but low adaptability to a step. Crawler type robots are suitable for rough terrain, and can be overcome if there are a few steps. However, because they cannot actively move the center of gravity, they are less adaptable to steep stairs and are more mobile on flat ground than wheel type robots. There was a problem of being low. In addition, the legged robot has the best adaptability to the stairs, but has the problem of extremely low mobility on flat ground.

As legged robots, for example, techniques disclosed in Patent Documents 1 and 2 are known.
The invention described in Patent Document 1 is a humanoid robot including an upper arm part, a lower arm part, a hand part, a waist part, a leg part, etc., and an external sensor is provided on the waist part, and the external sensor transmits multi-slit light to the floor. A light emitting means for irradiating the surface or the like, and an imaging means for imaging the irradiated floor surface or the like. The external sensor detects the floor surface and the like without receiving interference from the manipulator (upper arm, lower arm, and hand), and therefore can always stably measure the distance to the floor and the floor surface shape. .

In the invention described in Patent Document 2, a land marker is laid in the work space, and the position or direction of the land marker is detected by the optical sensor array to reach the work object. Further, when moving in an environment where the landing position is restricted, such as stairs, the gait is corrected by detecting a deviation between the target landing position and the actual landing position.
JP 2002-144278 A Japanese Patent Application Laid-Open No. 7-205085

By the way, in order to solve the problems of the wheel type, the crawler type and the leg type, a leg wheel type robot combining a leg type and a wheel type has been proposed.
The leg-wheel type robot includes a base, a plurality of legs connected to the base with a plurality of degrees of freedom, a drive wheel rotatably provided at the tip of each leg, a leg and a drive And an actuator for applying power for driving the wheel. Therefore, where there are obstacles such as steps, the legs can move within the range of degrees of freedom and can get over the steps, while when there are no obstacles such as flat ground, they can move by wheel running. it can.

As described above, in the leg wheel type robot, it is necessary to detect an obstacle in order to avoid the obstacle. However, as in the invention described in Patent Document 1, in the configuration in which the distance measuring sensor is provided on the base corresponding to the waist, When trying to detect an obstacle in the moving direction, there is a problem that the measurement area of the distance measuring sensor is blocked by the legs, and the obstacle cannot be detected or erroneously detected.
In addition, in the configuration in which the land marker laid in the work space is detected by the optical sensor array as in the invention described in Patent Document 2, it is necessary to lay the land marker in the work space in advance, and it is suitable for unknown steps. There was a problem that could not be done. For example, it cannot be used for the purpose of entering a place where people cannot enter during a disaster.

  Therefore, the present invention has been made paying attention to such an unsolved problem of the conventional technology, and can detect an obstacle without receiving interference from a leg, and can detect an unknown step. An object of the present invention is to provide a leg-wheel type robot that can realize high adaptability.

  [Invention 1] In order to achieve the above object, a leg-wheel type robot according to Invention 1 is provided with a base, a leg connected to the base with a degree of freedom, and a rotatable part on the leg. A leg-wheel type robot that moves by the rotation of the wheel, and is provided on the leg portion so as to be rotatable relative to the leg portion. A distance sensor, an actuator for applying power for rotating the distance measuring sensor, and an obstacle recognition unit for recognizing an obstacle based on measurement results measured at different rotation angles by the distance measuring sensor.

  With such a configuration, when the distance measuring sensor is rotated by the actuator, the measuring direction of the distance measuring sensor is relatively displaced with respect to the leg portion. Therefore, measurement is performed from different positions or angles with respect to obstacles such as steps. It can be performed. Then, the obstacle recognition unit recognizes the obstacle based on the measurement results measured at different rotation angles. Therefore, the shape of the obstacle can be recognized. In addition, since the distance measuring sensor is provided on the leg, the measurement area of the distance measuring sensor is not easily blocked by the leg. Thus, the obstacle can be recognized, the leg can move within the range of the degree of freedom, and the obstacle can be overcome. Therefore, the adaptability to an obstacle is high like a legged robot.

Moreover, on a flat ground, it can move by wheel drive. Therefore, the mobility on the flat ground is high like the wheel type robot.
Here, the distance measurement sensor only needs to be provided so that the measurement direction thereof is relatively displaced with respect to the leg, and specifically, for example, a joint near the base of the leg link. It may be provided so as to be rotatable coaxially, and may be provided so as to be rotatable about a line connecting a joint close to the base and the joint or axle on the opposite side, and is perpendicular to the joint close to the base and between the joints. It may be provided so as to be rotatable around an axis that is perpendicular to the connected line.

[Invention 2] Further, the leg wheel type robot of the invention 2 is the leg wheel type robot of the invention 1, wherein the leg portion is formed by connecting a plurality of links via joints, and the distance measuring sensor is the leg wheel type robot. It is provided in the link nearest to the leg tip among the links of the part.
With such a configuration, since the distance measuring sensor is provided on the link closest to the leg tip, the measurement area of the distance measuring sensor is more difficult to be blocked by the leg portion.

[Invention 3] Furthermore, the leg-wheel type robot of Invention 3 is the leg-wheel type robot according to any one of Inventions 1 and 2, wherein the actuator rotates the distance measuring sensor only in one direction.
With such a configuration, the distance sensor is rotated only in one direction by the actuator.

[Invention 4] Further, the leg-wheel type robot according to invention 4 is the leg-wheel type robot according to any one of inventions 1 and 2, wherein the actuator rotates the distance measuring sensor in a forward direction and a reverse direction.
With such a configuration, the distance measuring sensor is rotated in the forward direction and the reverse direction by the actuator.

  [Invention 5] The leg-wheel robot according to Invention 5 is the leg-wheel robot according to any one of Inventions 1 to 4, and further includes a second actuator that applies power for driving the leg portion or the wheel. And control means for controlling the second actuator based on the recognition result of the obstacle recognition means, the control means waiting for completion of measurement by the distance measuring sensor and starting drive control of the second actuator To do.

  With such a configuration, the measurement by the distance measuring sensor is performed where an obstacle such as a step exists, and the control unit waits for the completion of the measurement by the distance measuring sensor and starts the drive control of the second actuator. The Then, the second actuator is controlled based on the recognition result of the obstacle recognition means. When the second actuator is driven, power is applied to the legs or wheels, and the legs are driven within a range of degrees of freedom so that the vehicle can travel over obstacles or avoid obstacles. Therefore, since the raising / lowering control of the leg or the running control of the leg wheel type robot is performed while recognizing the unknown obstacle, high adaptability to the unknown obstacle can be realized.

  [Invention 6] Further, the leg-wheel type robot of the invention 6 is the leg-wheel type robot according to any one of the inventions 1 to 4, further including a second actuator for applying power for driving the leg portion or the wheel. And control means for controlling the second actuator based on the recognition result of the obstacle recognition means, and the control means starts driving control of the second actuator during measurement by the distance measuring sensor.

  With such a configuration, measurement by a distance measuring sensor is performed where an obstacle such as a step is present, and drive control of the second actuator is started by the control means during measurement by the distance measuring sensor. Then, the second actuator is controlled based on the recognition result of the obstacle recognition means. When the second actuator is driven, power is applied to the legs or wheels, and the legs are driven within a range of degrees of freedom so that the vehicle can travel over obstacles or avoid obstacles. Therefore, since the raising / lowering control of the leg or the running control of the leg wheel type robot is performed while recognizing the unknown obstacle, high adaptability to the unknown obstacle can be realized.

  [Invention 7] Furthermore, the leg-wheel type robot of the invention 7 is the leg-wheel type robot according to any one of the inventions 1 to 6, wherein the distance measuring sensor is an inner surface facing the inside of the base of the leg portion, and The leg portion is provided on one or both of the outer surfaces facing the outside of the base body.

[Invention 8] The leg-wheel robot according to Invention 8 is the leg-wheel robot according to any one of Inventions 1 to 7, wherein the distance measuring sensor is inclined at a predetermined angle around the yaw axis with respect to the leg. Is provided.
With such a configuration, when the leg is moved around the yaw axis in the direction in which the distance measuring sensor is inclined, an obstacle ahead can be recognized prior to the movement of the leg. .

[Invention 9] Furthermore, the leg-wheel type robot of the invention 9 is the leg-wheel type robot according to any one of the inventions 5 to 8, wherein the leg portion has a degree of freedom around the yaw axis and a pitch axis with respect to the base. The control means is connected with a degree of freedom around the roll axis, and the control means keeps the direction of the base body in a constant direction so that the traveling direction of the self-legged wheel robot coincides with the traveling direction of the wheels. In addition, the second actuator is controlled.
With this configuration, when the self-legged wheel robot is moving, the traveling direction of the self-legged robot matches the traveling direction of each wheel while maintaining the base of the leg-wheel robot at a fixed direction. Thus, the second actuator is controlled.

  [Invention 10] Furthermore, the leg-wheel type robot of the invention 10 is the leg-wheel type robot according to any one of the inventions 5 to 9, wherein the leg portion has a degree of freedom around the yaw axis and a pitch axis with respect to the base. A plurality of leg wheel mechanism units that are coupled to each other with a degree of freedom around a roll axis, and are configured by the leg units, the wheels, and the second actuators, Sometimes, when the base body rotates around the yaw axis at a predetermined rotation center position, the rotation center at the contact position between the arc trajectory drawn by the rotation center at the time of steering of each wheel and the rotation center at the time of steering is determined. The second actuator is controlled so that the movement direction and the traveling direction of each wheel coincide.

  With such a configuration, when turning, an arc trajectory drawn by the rotation center during steering of each wheel when the base body rotates around the yaw axis (vertical axis) at a predetermined rotation center position by the control means. The second actuator is controlled so that the direction of movement of the rotation center at the contact point between the wheel and the rotation center at the time of steering coincides with the traveling direction of each wheel.

  [Invention 11] On the other hand, in order to achieve the above object, an object recognition apparatus according to Invention 11 is an object recognition apparatus for recognizing a surface or a boundary of a surface on an object, and measures a distance to a measurement point on the object. A distance measuring sensor, a scanning means for scanning the distance measuring sensor, a measurement result acquiring means for acquiring a measurement result of the distance measuring sensor for the measurement points that can be measured in a scanning range of the scanning means, and the measurement result A coordinate conversion means for converting the measurement result acquired by the acquisition means into coordinates of an orthogonal coordinate system; and a line segment in the orthogonal coordinate system by Hough conversion based on the coordinates of at least two of the measurement points converted by the coordinate conversion means. And a recognition unit for recognizing a surface on the object or a boundary of the surface based on the line segment detected by the line segment detection unit.

With such a configuration, the distance measuring sensor can be scanned by the scanning unit. Therefore, at least the planar shape of the object can be grasped. Then, the measurement result acquisition unit acquires the measurement result of the distance measuring sensor for the measurement points that can be measured in the scanning range of the scanning unit, and the coordinate conversion unit converts the acquired measurement result into the coordinates of the orthogonal coordinate system. .
Next, a line segment in the orthogonal coordinate system is detected by the Hough transform based on the transformed coordinates of at least two measurement points.

As another method for detecting a line segment based on a plurality of measurement points, a least square method is known.
However, since the least square method detects a line segment by tracing each measurement point, a line segment that does not follow the surface on the object may be detected in a region where the measurement resolution is low. On the other hand, in the Hough transform, it is difficult to be affected by the measurement resolution, and a line segment relatively along the surface on the object can be detected even if the measurement resolution includes a low region.

  In the least-square method, line segments are detected by tracing each measurement point. Therefore, if measurement results vary due to the gloss of the measurement surface, etc. An area (hereinafter referred to as an error area) is detected as an oblique line segment, which is actually a flat line segment. On the other hand, the Hough transform is not easily affected by variations, and if the number of variations is small, the error region and the regions on both sides thereof can be detected as flat line segments.

  Further, the least square method has a problem as to whether to recognize a region from where to where is one continuous surface. In this case, for example, it is conceivable to recognize a point where the slope of the detected line segment changes abruptly as the boundary of the continuous surface. However, with this recognition method, the error region and the regions on both sides of the error region are actually 1 Two continuous areas are recognized as separate continuous areas. On the other hand, the Hough transform is not easily affected by variation, and if the number of variations is small, the error region and the regions on both sides thereof can be detected as one flat line segment.

When the line segment is detected by the Hough transform, the recognition unit recognizes the surface or the boundary of the surface on the object based on the detected line segment. Accordingly, it is possible to obtain a recognition result suitable for posture control of a robot that requires complicated posture control, such as a legged robot or a leg-wheel type robot.
Here, the scanning means may have any configuration as long as it scans the distance measuring sensor. For example, the scanning means scans the distance measuring sensor one-dimensionally so that the locus of the measurement points forms a line. Alternatively, the distance measuring sensor may be scanned two-dimensionally so that the locus of the measurement points forms a plane. In the former case, the planar shape of the object can be grasped, and in the latter case, the three-dimensional shape of the object can be grasped. Hereinafter, the same applies to the object recognition apparatuses of the inventions 12 and 17.

Moreover, as a scanning means, the following structure is employable, for example.
(1) Rotating mechanism The rotating mechanism is configured by rotating means for rotating the distance measuring sensor around at least one scanning axis that forms a predetermined angle with respect to the measuring direction of the distance measuring sensor.
(2) Moving mechanism The moving mechanism is configured by moving means for moving the distance measuring sensor in at least one scanning direction different from the measuring direction of the distance measuring sensor. The moving means may move the distance measuring sensor along a path including a path extending in the scanning direction. Hereinafter, the same applies to the object recognition apparatuses of the inventions 12 and 17.

  [Invention 12] The object recognition apparatus of the invention 12 is an object recognition apparatus for recognizing a surface or a boundary of a surface on an object, the distance measuring sensor for measuring a distance to a measurement point on the object, and the measurement. Scanning means for scanning the distance sensor, measurement result acquiring means for acquiring the measurement results of the distance measuring sensor for the measurement points that can be measured in the scanning range of the scanning means, and measurement results acquired by the measurement result acquiring means Coordinate conversion means for converting into coordinates in an orthogonal coordinate system, inter-measurement point interpolation means for interpolating between the measurement points converted by the coordinate conversion means, and points on the line obtained by the inter-measurement point interpolation means Line segment detection means for detecting a line segment in the orthogonal coordinate system by Hough transform based on the coordinates of the object, and recognition means for recognizing a surface or a boundary of the surface on the object based on the line segment detected by the line segment detection means With.

With such a configuration, the distance measuring sensor can be scanned by the scanning unit. Therefore, at least the planar shape of the object can be grasped. Then, the measurement result acquisition unit acquires the measurement result of the distance measuring sensor for the measurement points that can be measured in the scanning range of the scanning unit, and the coordinate conversion unit converts the acquired measurement result into the coordinates of the orthogonal coordinate system. .
Next, the inter-measurement point interpolation means interpolates between the converted measurement points, and the line segment detection means detects the line segment in the orthogonal coordinate system by Hough transform based on the coordinates of the point on the obtained line. The

As another method for detecting a line segment based on a plurality of measurement points, a least square method is known.
However, since the least square method detects a line segment by tracing each measurement point, a line segment that does not follow the surface on the object may be detected in a region where the measurement resolution is low. On the other hand, in the Hough transform, it is difficult to be affected by the measurement resolution, and a line segment relatively along the surface on the object can be detected even if the measurement resolution includes a low region.

  In addition, in the least square method, the line segment is detected by tracing each measurement point. Therefore, when the measurement result varies due to the influence of the gloss of the measurement surface, the error area is actually a flat line segment. However, it is detected as an oblique line segment. On the other hand, the Hough transform is not easily affected by variations, and if the number of variations is small, the error region and the regions on both sides thereof can be detected as flat line segments.

  Further, the least square method has a problem as to whether to recognize a region from where to where is one continuous surface. In this case, for example, it is conceivable to recognize a point where the slope of the detected line segment changes abruptly as the boundary of the continuous surface. However, with this recognition method, the error region and the regions on both sides of the error region are actually 1 Two continuous areas are recognized as separate continuous areas. On the other hand, the Hough transform is not easily affected by variation, and if the number of variations is small, the error region and the regions on both sides thereof can be detected as one flat line segment.

When the line segment is detected by the Hough transform, the recognition unit recognizes the surface or the boundary of the surface on the object based on the detected line segment. Accordingly, it is possible to obtain a recognition result suitable for posture control of a robot that requires complicated posture control, such as a legged robot or a leg-wheel type robot.
Here, the interpolation includes connecting the measurement points with a line and approximating the measurement points with a line. The measurement points do not necessarily have to be located on the line, and adjacent measurement points are not necessarily included. It is not necessary to target points. Hereinafter, the same applies to the object recognition device of the invention 19 and the object recognition method of the invention 28.
The line includes a straight line, a line segment, a multi-order curve, and other curves. Hereinafter, the same applies to the object recognition device of the invention 19 and the object recognition method of the invention 28.

[Invention 13] Further, the object recognition device of Invention 13 is the object recognition device of any one of Inventions 11 and 12, wherein the recognition means is based on the coordinates of the end points of the line segment detected by the line segment detection means. Recognize the boundary of the surface on the object.
With such a configuration, the recognition means recognizes the boundary of the surface on the object based on the coordinates of the end points of the detected line segment.

  [Invention 14] The object recognition apparatus according to Invention 14 is the object recognition apparatus according to any one of Inventions 11 to 13, wherein the scanning means measures the measurement in a first scanning direction different from the measurement direction of the distance measuring sensor. A first scanning unit that scans the distance sensor; and a second scanning unit that scans the distance measuring sensor in a second scanning direction different from the measurement direction and the first scanning direction. The measurement result of the distance measuring sensor is acquired for the measurement points that can be measured in the scanning range of the first scanning means and the second scanning means.

  With this configuration, the first scanning unit can scan the distance measuring sensor in the first scanning direction, and the second scanning unit can scan the distance measuring sensor in the second scanning direction. Therefore, the three-dimensional shape of the object can be grasped. Then, the measurement result acquisition means acquires the measurement result of the distance measuring sensor for the measurement points that can be measured in the scanning range of the first scanning means and the second scanning means.

Here, as the first scanning unit and the second scanning unit, for example, the following configuration can be adopted.
(1) Rotation mechanism First rotation means for rotating the distance measuring sensor around a first scanning axis that forms a predetermined angle with respect to the measurement direction of the distance measuring sensor, and the measurement direction and the first scanning axis. And a second rotating means for rotating the distance measuring sensor around a second scanning axis forming a predetermined angle.
(2) Moving mechanism First moving means for moving the distance measuring sensor in a first scanning direction different from the measuring direction of the distance measuring sensor, and a second scanning direction different from the measuring direction and the first scanning direction. It comprises a second moving means for moving the distance measuring sensor. The first moving unit may move the distance measuring sensor along a first path including a path extending in the first scanning direction, and the second moving unit extends in the second scanning direction. The distance measuring sensor may be moved along a second route including a route to be performed. The same applies to (3) and (4) below.
(3) Combination of rotating mechanism and moving mechanism Rotating means for rotating the distance measuring sensor around a scanning axis forming a predetermined angle with respect to the measuring direction of the distance measuring sensor, and scanning different from the axial direction of the scanning axis And a moving means for moving the distance measuring sensor in the direction.
(4) A combination of a moving mechanism and a rotating mechanism The moving means for moving the distance measuring sensor in a scanning direction different from the measuring direction of the distance measuring sensor, and the scanning axis about a predetermined angle with respect to the scanning direction It is the structure which consists of a rotation means to rotate a ranging sensor. The same applies to the object recognition apparatus of the invention 21 below.

[Invention 15] The object recognition device of Invention 15 is the object recognition device of Invention 14, wherein the recognition means recognizes a surface on the object based on the coordinates of the end points of the line segment detected by the line segment detection means. To do.
With such a configuration, the surface on the object is recognized by the recognition unit based on the coordinates of the end points of the detected line segment.

  [Invention 16] The object recognition apparatus according to Invention 16 is the object recognition apparatus according to any one of Inventions 14 and 15, wherein the first scanning means has a first scanning axis that forms a predetermined angle with respect to the measurement direction. A first rotating means for rotating the distance measuring sensor around, the second scanning means being configured to rotate the distance measuring sensor around a second scanning axis that forms a predetermined angle with respect to the measuring direction and the first scanning axis; The measurement result acquisition means outputs the measurement result of the distance measurement sensor for each predetermined unit angle of the first rotation means while rotating the distance measurement sensor by the first rotation means. A predetermined unit angle of the first rotating means is obtained by performing a second scan in which the first scanning to be acquired is performed at predetermined unit angles of the second rotating means while rotating the distance measuring sensor by the second rotating means. Your And obtaining the measurement results for each predetermined unit angle of the second rotation means.

  With such a configuration, the distance measuring sensor can be rotated around the first scanning axis by the first rotating means, and the distance measuring sensor can be rotated around the second scanning axis by the second rotating means. Therefore, the three-dimensional shape of the object can be grasped. Then, the second scanning is performed by the measurement result acquisition unit, whereby measurement results for each predetermined unit angle of the first rotation unit and for each predetermined unit angle of the second rotation unit are acquired. In the second scanning, the first scanning is performed for each predetermined unit angle of the second rotating means while the distance measuring sensor is rotated by the second rotating means. In the first scan, a measurement result is acquired for each predetermined unit angle of the first rotating means while rotating the distance measuring sensor by the first rotating means.

  [Invention 17] Further, the object recognition device of the invention 17 is an object recognition device for recognizing a surface or a boundary of a surface on the object, the distance measuring sensor for measuring the distance to the measurement point on the object, and the measurement. A scanning unit that scans the distance sensor, a measurement result acquisition unit that acquires a measurement result of the distance measuring sensor for the measurement point that can be measured in a scanning range of the scanning unit, and a measurement result acquired by the measurement result acquisition unit. A first feature detecting unit for detecting a feature on the object based on the image, an imaging unit for capturing an image including the measurement point that can be measured in a scanning range of the scanning unit, and an object based on the image captured by the imaging unit. Second feature detection means for detecting the upper feature, and recognition means for recognizing a surface or a boundary of the surface on the object based on detection results of the first feature detection means and the second feature detection means.

With such a configuration, the distance measuring sensor can be scanned by the scanning unit. Therefore, at least the planar shape of the object can be grasped. Then, the measurement result acquisition means acquires the measurement result of the distance measuring sensor for the measurement points that can be measured in the scanning range of the scanning means, and the first feature detection means determines the feature on the object based on the acquired measurement result. Detected.
In addition, an image including a measurement point that can be measured within the scanning range of the scanning unit is captured by the imaging unit, and a feature on the object is detected based on the captured image by the second feature detection unit.

Then, the recognition unit recognizes the surface or the boundary of the surface on the object based on the detection results of the first feature detection unit and the second feature detection unit.
Here, the features on the object include, for example, points indicating features on the object, straight lines, line segments, multi-order curves, circles, ellipses and other curves, planes, curved surfaces and other surfaces, cubes, spheres and other three-dimensional shapes. Features are included. The same applies to the object recognition method of the invention 29 below.

  [Invention 18] The object recognition apparatus according to Invention 18 is the object recognition apparatus according to Invention 17, wherein the first feature detection means converts the measurement result acquired by the measurement result acquisition means into coordinates in an orthogonal coordinate system. Conversion means; and line segment detection means for detecting line segments in the orthogonal coordinate system by Hough transform based on the coordinates of at least two measurement points converted by the coordinate conversion means; and the recognition means, Based on the line segment detected by the line segment detection means and the detection result of the second feature detection means, the surface on the object or the boundary of the surface is recognized.

If it is such a structure, the acquired measurement result will be converted into the coordinate of a rectangular coordinate system by a coordinate conversion means.
Then, a line segment in the orthogonal coordinate system is detected by the Hough transform based on the transformed coordinates of at least two measurement points.
As another method for detecting a line segment based on a plurality of measurement points, a least square method is known.

However, since the least square method detects a line segment by tracing each measurement point, a line segment that does not follow the surface on the object may be detected in a region where the measurement resolution is low. On the other hand, in the Hough transform, it is difficult to be affected by the measurement resolution, and a line segment relatively along the surface on the object can be detected even if the measurement resolution includes a low region.
In addition, in the least square method, the line segment is detected by tracing each measurement point. Therefore, when the measurement result varies due to the influence of the gloss of the measurement surface, the error area is actually a flat line segment. However, it is detected as an oblique line segment. On the other hand, the Hough transform is not easily affected by variations, and if the number of variations is small, the error region and the regions on both sides thereof can be detected as flat line segments.

  Further, the least square method has a problem as to whether to recognize a region from where to where is one continuous surface. In this case, for example, it is conceivable to recognize a point where the slope of the detected line segment changes abruptly as the boundary of the continuous surface. However, with this recognition method, the error region and the regions on both sides of the error region are actually 1 Two continuous areas are recognized as separate continuous areas. On the other hand, the Hough transform is not easily affected by variation, and if the number of variations is small, the error region and the regions on both sides thereof can be detected as one flat line segment.

  When the line segment is detected by the Hough transform, the recognition unit recognizes the surface or the boundary of the surface on the object based on the detected line segment and the detection result of the second feature detection unit. Therefore, the technique of Non-Patent Document 1 can generate only simple map information for movement control of a crawler type robot that does not require complicated posture control. Since at least the planar shape of an object can be grasped as a boundary, a recognition result suitable for posture control of a robot that requires complicated posture control such as a legged robot or a leg-wheel type robot can be obtained. .

  [Invention 19] Further, the object recognition device of Invention 19 is the object recognition device of Invention 17, wherein the first feature detection means is a coordinate for converting the measurement result acquired by the measurement result acquisition means into coordinates of an orthogonal coordinate system. A conversion means, an inter-measurement point interpolation means for interpolating between the measurement points converted by the coordinate conversion means, and the Hough transform based on the coordinates of the points on the line obtained by the inter-measurement point interpolation means. A line segment detecting means for detecting a line segment in an orthogonal coordinate system, wherein the recognizing means is a surface on the object based on the line segment detected by the line segment detecting means and the detection result of the second feature detecting means. Or recognize the boundary of the face.

If it is such a structure, the acquired measurement result will be converted into the coordinate of a rectangular coordinate system by a coordinate conversion means, and between the measured points will be interpolated by a line by the inter-measurement point interpolation means.
Then, a line segment in the orthogonal coordinate system is detected by the Hough transform based on the coordinates of the obtained point on the line. It should be noted that there are advantages similar to those described above over the least square method.

  When the line segment is detected by the Hough transform, the recognition unit recognizes the surface or the boundary of the surface on the object based on the detected line segment and the detection result of the second feature detection unit. Therefore, as described above, it is possible to obtain a recognition result suitable for posture control of a robot that requires complicated posture control, such as a legged robot or a leg-wheel type robot.

  [Invention 20] Further, the object recognition device of Invention 20 is the object recognition device of Invention 17, wherein the first feature detection means is a coordinate for converting the measurement result acquired by the measurement result acquisition means into coordinates of an orthogonal coordinate system. Inclination calculation for calculating the inclination at the measurement point in the orthogonal coordinate system based on the coordinates of the measurement point and the coordinates of the measurement points in the vicinity thereof for each measurement point converted by the conversion means and the coordinate conversion means And an appearance frequency calculating means for calculating the appearance frequency of each inclination with respect to the total number of inclinations calculated by the inclination calculating means, and the recognition means is the appearance frequency calculated by the appearance frequency calculating means and the converted The surface on the object or the boundary of the surface is recognized based on the coordinates of each measurement point and the detection result of the second feature detection means.

  If it is such a structure, the acquired measurement result will be converted into the coordinate of a rectangular coordinate system by the coordinate conversion means, and the coordinates of the measurement point and its surroundings will be obtained for each converted measurement point by the inclination calculation means. The inclination at the measurement point in the orthogonal coordinate system is calculated based on the coordinates of the measurement points, and the appearance frequency calculating means calculates the appearance frequency of each inclination with respect to the calculated total number of inclinations.

  When the appearance frequency of each inclination is calculated, the recognition unit calculates the surface on the object or the boundary of the surface based on the calculated appearance frequency, the converted coordinates of each measurement point, and the detection result of the second feature detection unit. Is recognized. Therefore, as described above, it is possible to obtain a recognition result suitable for posture control of a robot that requires complicated posture control, such as a legged robot or a leg-wheel type robot.

  Here, the inclination calculation means, for example, approximates a regression line with respect to a plurality of measurement points by a known least square method, calculates an inclination from the regression line, or, in an orthogonal coordinate system, a plurality of continuous in one axial direction. Inclination is calculated using the difference value of the coordinates of the two measurement points at both ends of the measurement point and the difference value of the coordinates of the measurement points of the two ends of the plurality of measurement points continuous in the other axial direction. Can do.

  [Invention 21] Further, the object recognition device of Invention 21 is the object recognition device of any one of Inventions 17 to 20, wherein the scanning means measures the measurement in a first scanning direction different from the measurement direction of the distance measuring sensor. A first scanning unit that scans the distance sensor; and a second scanning unit that scans the distance measuring sensor in a second scanning direction different from the measurement direction and the first scanning direction. The measurement result of the distance measuring sensor is acquired for the measurement points that can be measured in the scanning range of the first scanning means and the second scanning means.

  With this configuration, the first scanning unit can scan the distance measuring sensor in the first scanning direction, and the second scanning unit can scan the distance measuring sensor in the second scanning direction. Therefore, the three-dimensional shape of the object can be grasped. Then, the measurement result acquisition means acquires the measurement result of the distance measuring sensor for the measurement points that can be measured in the scanning range of the first scanning means and the second scanning means.

  [Invention 22] Further, the object recognition device of Invention 22 is the object recognition device of Invention 21, wherein the first scanning means is the distance measuring sensor around a first scanning axis forming a predetermined angle with respect to the measurement direction. The second scanning means rotates the distance measuring sensor around a second scanning axis that forms a predetermined angle with respect to the measurement direction and the first scanning axis. The measurement result acquisition means performs a first scan for acquiring the measurement result of the distance measurement sensor for each predetermined unit angle of the first rotation means while rotating the distance measurement sensor by the first rotation means. By performing the second scanning performed at every predetermined unit angle of the second rotating means while rotating the distance measuring sensor by the second rotating means, the second rotation is performed at every predetermined unit angle of the first rotating means. hand Acquiring the measurement results for each predetermined unit angle.

  With such a configuration, the distance measuring sensor can be rotated around the first scanning axis by the first rotating means, and the distance measuring sensor can be rotated around the second scanning axis by the second rotating means. Therefore, the three-dimensional shape of the object can be grasped. Then, the second scanning is performed by the measurement result acquisition unit, whereby measurement results for each predetermined unit angle of the first rotation unit and for each predetermined unit angle of the second rotation unit are acquired. In the second scanning, the first scanning is performed for each predetermined unit angle of the second rotating means while the distance measuring sensor is rotated by the second rotating means. In the first scan, a measurement result is acquired for each predetermined unit angle of the first rotating means while rotating the distance measuring sensor by the first rotating means.

  [Invention 23] The object recognition apparatus of Invention 23 is the object recognition apparatus of any one of Inventions 17 to 20, comprising a plurality of the distance measuring sensors and the scanning means, and each of the scanning means includes the scanning means. Are scanned in a first scanning direction different from the measurement direction of the distance measuring sensor, and each distance measuring sensor is scanned in a second scanning direction different from the measurement direction and the first scanning direction. Is arranged.

  With such a configuration, each scanning unit can scan each distance measuring sensor arranged in the second scanning direction in the first scanning direction. Therefore, the three-dimensional shape of the object can be grasped. And the measurement result of each ranging sensor is acquired by the measurement result acquisition means about the measurement point which can be measured in the scanning range of a scanning means.

  [Invention 24] Further, the object recognition device according to Invention 24 is the object recognition device according to any one of Inventions 17 to 23, wherein the first feature detection means is an object based on the measurement result acquired by the measurement result acquisition means. The upper feature point is detected, and the second feature detection unit includes an image line segment detection unit that detects a line segment from an image captured by the imaging unit, and the recognition unit is based on the imaging unit. In the coordinate system, the surface on the object or the boundary of the surface is recognized based on the positional relationship between the line segment detected by the image line segment detection unit and the feature point detected by the first feature detection unit.

If it is such a structure, the feature point on an object will be detected by the 1st feature detection means based on the acquired measurement result, and a line segment will be detected from the imaged image by the image line segment detection means. .
Then, the recognition unit recognizes the surface or the boundary of the surface on the object based on the positional relationship between the detected line segment and the detected feature point in the coordinate system based on the imaging unit.

  [Invention 25] Further, the object recognition device of Invention 25 is the object recognition device of Invention 24, wherein the recognition means calculates the line segment and the line segment for each line segment detected by the image line segment detection means. Corresponding to the feature points existing within a predetermined distance from the extended straight line, grouping the line segments associated with the same feature points, and based on the coordinates of the end points of the line segments belonging to the same group Recognize the upper face or face boundary.

  With such a configuration, the recognition means associates each detected line segment with the line segment and a feature point existing within a predetermined distance from the straight line obtained by extending the line segment, and the same feature The line segments associated with the points are grouped, and the surface on the object or the boundary of the surface is recognized based on the coordinates of the end points of the line segments belonging to the same group.

  [Invention 26] Further, the object recognition device of Invention 26 is the object recognition device of any one of Inventions 24 and 25, wherein a plane composed of two predetermined axes in an orthogonal coordinate system with reference to the distance measuring sensor, The distance measuring sensor and the imaging means are arranged so that a plane composed of two predetermined axes in an orthogonal coordinate system based on the imaging means is parallel.

  [Invention 27] On the other hand, in order to achieve the above object, the object recognition method of Invention 27 recognizes a surface on the object or a boundary of the surface using a distance measuring sensor that measures a distance to a measurement point on the object. An object recognition method, a scanning step of scanning the distance measuring sensor, a measurement result acquiring step of acquiring a measurement result of the distance measuring sensor for the measurement points that can be measured in a scanning range of the scanning step, and the measurement A coordinate conversion step for converting the measurement result acquired in the result acquisition step into a coordinate in the orthogonal coordinate system, and a line in the orthogonal coordinate system by Hough conversion based on the coordinates of the at least two measurement points converted in the coordinate conversion step. A line segment detecting step for detecting a segment, and a recognition step for recognizing a surface or a boundary of the surface on the object based on the line segment detected in the line segment detecting step.

  Here, the scanning step may be any method as long as it scans the distance measuring sensor. For example, the distance measuring sensor may be scanned one-dimensionally so that the locus of the measurement points forms a line. Alternatively, the distance measuring sensor may be scanned two-dimensionally so that the locus of the measurement points forms a plane. In the former case, the planar shape of the object can be grasped, and in the latter case, the three-dimensional shape of the object can be grasped. The same applies to the object recognition methods of the inventions 28 and 29 below.

  [Invention 28] The object recognition method of the invention 28 is an object recognition method for recognizing a surface or a boundary of a surface on an object using a distance measuring sensor for measuring a distance to a measurement point on the object, A scanning step for scanning the distance measuring sensor, a measurement result acquiring step for acquiring a measurement result of the distance measuring sensor for the measurement points that can be measured in the scanning range of the scanning step, and a measurement result acquired in the measurement result acquiring step On the line obtained by the coordinate conversion step for converting the coordinates into the coordinates of the orthogonal coordinate system, the inter-measurement point interpolation step for interpolating between the measurement points converted by the coordinate conversion step, and the inter-measurement point interpolation step A line segment detection step for detecting a line segment in the orthogonal coordinate system by Hough transform based on the coordinates of the point, and a surface on the object based on the line segment detected in the line segment detection step. And a recognition step recognizes the boundary of the surface.

  [Invention 29] Further, the object recognition method of the invention 29 is an object recognition method for recognizing a surface or a boundary of a surface on an object by using a distance measuring sensor for measuring a distance to a measurement point on the object. A scanning step for scanning the distance measuring sensor, a measurement result acquiring step for acquiring a measurement result of the distance measuring sensor for the measurement points that can be measured in the scanning range of the scanning step, and a measurement result acquired in the measurement result acquiring step A first feature detection step for detecting a feature on the object based on the image, an imaging step for capturing an image including the measurement point that can be measured in a scanning range of the scanning step, and an image captured in the imaging step A second feature detecting step for detecting a feature on the object; a surface on the object based on the detection results of the first feature detecting step and the second feature detecting step; The boundary surface and a recognizing step.

  As described above, according to the leg-wheel type robot of the first aspect, since the distance measuring sensor is provided on the leg part, it is possible to detect an obstacle while reducing the interference of the leg part, and to measure the distance. Since an unknown obstacle is recognized using a sensor, an effect that high adaptability to an unknown obstacle can be realized is obtained. Furthermore, since the obstacle is recognized based on the measurement results measured at different rotation angles by the distance measuring sensor, an effect that the shape of the obstacle can be recognized is also obtained.

Furthermore, according to the leg-wheel type robot of the invention 2, since the distance measuring sensor is provided at the link closest to the leg tip, there is an effect that it is possible to detect an obstacle by further reducing the interference of the leg portion. can get.
Furthermore, according to the leg-wheel type robot of the invention 5 or 6, since the lift control of the leg portion or the travel control of the leg-wheel type robot is performed while recognizing the unknown obstacle using the distance measuring sensor, the unknown obstacle The effect that high adaptability can be realized is obtained.

Furthermore, according to the leg-wheel type robot of the eighth aspect of the invention, there is an effect that it is possible to recognize an obstacle ahead of the movement of the leg portion.
Furthermore, according to the leg-wheel type robot of the invention 9, the leg-wheel type robot can be moved in a free direction regardless of the direction thereof, so that a quick movement in each direction can be realized. It is possible to perform activities even in areas where it is difficult to change the direction of the leg wheel type robot, such as a narrow and intricate area where each component of the leg wheel type robot is hindered and cannot turn. .

  Furthermore, according to the leg-wheel type robot of the tenth aspect, when turning, the arc drawn by the rotation center at the time of steering of each wheel when the base body of the leg-wheel type robot rotates around the yaw axis at a predetermined rotation center position. Since the direction of movement of the center of rotation at the contact point between the track and the center of rotation at the time of steering can coincide with the traveling direction of each wheel, the leg wheel type robot can be moved back and forth at a predetermined turning center position. The effect that a turn (a turn equivalent to a super-trust turn by a crawler or the like) can be performed is obtained. Further, by setting the center position of the base body as the rotation center position when rotating, the leg wheel type robot can be turned with the minimum turning radius.

  On the other hand, according to the object recognition device of the invention 11, 12, 18 or 19, it is possible to grasp at least a planar shape of an object as a surface on the object or a boundary of the surface. As described above, it is possible to obtain a recognition result suitable for posture control of a robot that requires complicated posture control. In addition, because line segments are detected by Hough transform, when object recognition is performed using a two-dimensional distance measuring device using a distance measuring sensor, the possibility that the recognition accuracy will decrease due to a decrease in measurement resolution or variations in measurement results is reduced. The effect that it can do is also acquired.

Furthermore, according to the object recognition device of the twelfth or nineteenth aspect, since the line segment is detected based on the coordinates of the points on the line obtained by interpolating between the measurement points, the measurement resolution decreases or the measurement results vary. Even if this occurs, it is possible to obtain a relatively accurate recognition result, and to further reduce the possibility that the recognition accuracy is lowered.
Furthermore, according to the object recognition device of the thirteenth aspect, there is an effect that the boundary of the surface on the object can be recognized relatively accurately.

Furthermore, according to the object recognition device of the invention 14, since the three-dimensional shape of the object can be grasped as a surface on the object or a boundary between the surfaces, complicated posture control such as a legged robot or a leg wheel type robot can be performed. It is possible to obtain a recognition result more suitable for posture control of a robot that requires
Furthermore, according to the object recognition device of the fifteenth aspect, an effect that the surface on the object can be recognized relatively accurately is obtained.

Furthermore, according to the object recognition apparatus of the sixteenth aspect, since the rotation mechanism for rotating the distance measuring sensor is adopted, the space required for scanning is smaller than that of the moving mechanism, and the mechanism for scanning becomes simple. And the effect that a high-speed scanning is realizable is acquired.
Furthermore, according to the object recognition device of the seventeenth aspect, in addition to the distance measurement sensor, the feature on the object is detected using an imaging means of a different system, and the surface on the object is detected based on the two detection results. Alternatively, since the boundary of the surface is recognized, the shortcomings of the method using the distance measuring sensor can be compensated for by the method using the imaging means, and the recognition accuracy decreases when the object is recognized by the two-dimensional distance measuring device using the distance measuring sensor. The effect that it is possible to reduce the possibility of doing is obtained. In addition, since it is not necessary to increase the number of scans of the scanning means, the effect that the measurement time can be shortened is also obtained.

  Furthermore, according to the object recognition device of the twentieth aspect, since at least a planar shape of an object can be grasped as a surface on the object or a boundary between surfaces, a complicated posture such as a legged robot or a legged wheel type robot can be obtained. An effect is obtained that a recognition result suitable for posture control of a robot that requires control can be obtained. In addition, since the surface on the object or the boundary of the surface is recognized based on the appearance frequency of the inclination at the measurement point and the coordinates of each measurement point, when the object recognition is performed by the two-dimensional distance measuring device using the distance measuring sensor. In addition, there is an effect that the possibility that the recognition accuracy is lowered can be further reduced.

Furthermore, according to the object recognition device of the invention 21 or 23, since the three-dimensional shape of the object can be grasped as a surface on the object or a boundary between the surfaces, it is complicated as in a legged robot or a leg wheel type robot. An effect is obtained that a recognition result more suitable for posture control of a robot that requires posture control can be obtained.
Furthermore, according to the object recognition device of the invention 22, since the rotation mechanism for rotating the distance measuring sensor is adopted, the space required for scanning is smaller than that of the moving mechanism, and the mechanism for scanning becomes simple. And the effect that a high-speed scanning is realizable is acquired.

Furthermore, according to the object recognition device of the invention 24, a surface on the object or a boundary of the surface is recognized based on the positional relationship between the line segment detected from the image and the feature point detected from the measurement result of the distance measuring sensor. Therefore, an effect that the possibility that the recognition accuracy is lowered can be further reduced.
Furthermore, according to the object recognition device of the invention 25, even if it is detected as a plurality of line segments from the captured image due to the influence of contrast or the like, it is actually measured by the distance measuring sensor. Based on the correspondence with the feature points detected from the results, multiple line segments are grouped as a single line segment and the surface or boundary of the surface on the object is recognized, further reducing the possibility of reduced recognition accuracy The effect that it can do is acquired.

On the other hand, according to the object recognition method of the invention 27, an effect equivalent to that of the object recognition device of the invention 11 can be obtained.
Furthermore, according to the object recognition method of the invention 28, an effect equivalent to that of the object recognition device of the invention 12 can be obtained.
Furthermore, according to the object recognition method of the invention 29, an effect equivalent to that of the object recognition device of the invention 17 can be obtained.

[First Embodiment]
Hereinafter, a first embodiment of the present invention will be described with reference to the drawings. 1 to 11 are views showing a first embodiment of a leg-wheel type robot according to the present invention.
First, the configuration of a leg wheel type robot 100 to which the present invention is applied will be described.
FIG. 1 is a front view of a leg wheel type robot 100.

FIG. 2 is a side view of the leg wheel type robot 100.
As shown in FIGS. 1 and 2, the leg-wheel type robot 100 includes a base body 10 and four leg portions 12 coupled to the base body 10.
In front of the base 10, two leg portions 12 are coupled to a symmetrical position via a rotary joint 14. In addition, two legs 12 are connected to the rear side of the base body 10 via a rotary joint 14 at a symmetrical position. The rotary joint 14 rotates with the direction orthogonal to the bottom surface of the leg wheel type robot 100 as an axial direction. That is, it rotates around the yaw axis.

  Each leg portion 12 is provided with two rotary joints 16 and 18. The rotary joint 14 rotates with the lower side as the axial direction, and the rotary joints 16 and 18 rotate with the direction orthogonal to the side surface of the leg wheel type robot 100 as the axial direction when the rotary joint 14 is in the state of FIG. . That is, when the rotary joint 14 is in the state of FIG. 1, it rotates about the pitch axis, and when the rotary joint 14 is rotated 90 degrees from the state of FIG. 1, it rotates about the roll axis. Each leg 12 has three degrees of freedom.

A driving wheel 20 is rotatably provided at the tip of each leg 12 with the same axial direction as the rotary joints 16 and 18. The drive wheel 20 is rotated around the yaw axis by the rotation of the rotary joint 14. That is, by controlling the rotation of the rotary joint 14, steering control during traveling movement is performed.
Of the links of each leg 12, an in-plane scanning leg tip sensor 38 that measures the distance to the obstacle is provided on the leg tip side link relative to the rotary joint 18 (hereinafter referred to as the most advanced link). It is provided so as to be rotatable so that the angle formed by the measurement direction changes with respect to the extending direction.

On the other hand, a horizontal laser 26 that irradiates a horizontal laser beam is provided in the upper center of the front surface of the substrate 10. In addition, vertical lasers 28 and 30 for irradiating vertical surface laser light are respectively provided on the center left and right of the front surface of the substrate 10.
A camera 32 that captures an image including reflected light of a horizontal plane laser beam and a vertical plane laser beam is provided at the lower center of the front surface of the substrate 10.

The horizontal laser 26 is provided so as to be inclined downward by a predetermined angle so that the camera 32 can capture an image including the reflected light of the horizontal laser beam. Similarly, the vertical laser 28 is tilted to the right by a predetermined angle so that the camera 32 can capture an image including reflected light of the vertical plane laser beam, and the vertical laser 30 is tilted to the left by a predetermined angle. ing.
Obstacle sensors 34 and 36 for detecting an obstacle are provided on the left and right of the camera 32, respectively.

FIG. 3 is a diagram illustrating the configuration of the obstacle sensors 34 and 36.
As shown in FIG. 3A, the obstacle sensors 34 and 36 can be configured by arranging a plurality of ultrasonic ranging sensors having low directivity in an array. Further, as shown in FIG. 3B, a plurality of infrared ranging sensors having high directivity can be arranged in an array. It is not limited to the configuration arranged in an array, and may be configured as a single unit. Moreover, you may comprise with the area sensor which arranged the ultrasonic ranging sensor or the infrared ranging sensor on the several plane. Thereby, the obstacle which exists on the movement path | route of the leg wheel type robot 100 can be roughly detected.

Next, the mounting structure of the in-plane scanning leg tip sensor 38 will be described.
FIG. 4 is a view showing the mounting structure of the in-plane scanning leg tip sensor 38 and is a front view of the leg 12.
FIG. 5 is a side view of the leg portion 12 showing the mounting structure of the in-plane scanning leg tip sensor 38.

As shown in FIG. 4, a reduction gear 80 is provided at the most distal link of each leg 12 so as to have a rotation axis in the same direction as the rotation axis of the rotary joint 18. The in-plane scanning leg tip sensor 38 is fixed to the output side rotation shaft of the speed reducer 80, and the motor 82 is fixed to the input side rotation shaft. The in-plane scanning leg tip sensor 38 is located on the outer surface of the leg portion 12 facing the outside of the base body 10.
Therefore, as shown in FIG. 5, the in-plane scanning leg tip sensor 38 rotates around the rotation axis in the same direction as the rotation axis of the rotary joint 18 by the rotation of the motor 82. At this time, since the angle formed by the measurement direction of the in-plane scanning leg tip sensor 38 with respect to the extending direction of the leg portion 12 changes, the measurement can be performed from a different position or angle with respect to the obstacle.

Next, the movement control system of the leg wheel type robot 100 will be described.
FIG. 6 is a block diagram showing a movement control system of the leg wheel type robot 100.
As shown in FIG. 6, joint motors 40 that rotationally drive the rotary joints 14 to 18 are provided at the rotary joints 14 to 18 of the leg portions 12, respectively. Each joint motor 40 is provided with an encoder 42 that detects the rotational angle position of the joint motor 40, and a driver 44 that controls the driving of the joint motor 40 based on the motor command signal and the output signal of the encoder 42.

A wheel motor 50 that rotationally drives the drive wheel 20 is provided on the drive wheel 20 of each leg 12. Each wheel motor 50 is provided with an encoder 52 that detects the rotational angle position of the wheel motor 50, and a driver 54 that controls the driving of the wheel motor 50 based on the motor command signal and the output signal of the encoder 52.
The leg wheel type robot 100 further performs wireless communication with the CPU 60, the three-axis attitude sensor 70 that detects the attitude of the leg wheel type robot 100, the vision processor 72 that processes the image signal of the camera 32, and an external PC. The wireless communication unit 74 is configured to include a vision processor 72, a wireless communication unit 74, a hub 76 that relays input / output of the CPU 60, and a speaker 78 that outputs a warning sound or the like.

The triaxial attitude sensor 70 includes a gyroscope or an acceleration sensor, or both, and detects the inclination of the attitude of the leg wheel type robot 100 with respect to the ground axis.
The CPU 60 outputs motor command signals to the drivers 44 and 54 via the motor command output I / F 61 and inputs output signals of the encoders 42 and 52 via the angle fetch I / F 62. Although not shown, a motor command signal is output to the driver of the motor 82 via the motor command output I / F 61.

The CPU 60 inputs sensor signals from the in-plane scanning leg tip sensor 38, the obstacle sensor 34, and the triaxial posture sensor 70 via the sensor input I / F 63, respectively. Further, signals are input / output to / from the hub 76 via the communication I / F 64, and an audio signal is output to the speaker 78 via the sound output I / F 65.
Next, processing executed by the CPU 60 will be described.

The CPU 60 activates a control program stored in a predetermined area such as a ROM, and executes the elevation control process shown in the flowchart of FIG. 7 according to the control program.
FIG. 7 is a flowchart showing the elevation control process.
The raising / lowering control process is a process for performing the raising / lowering control of the leg portion 12. When the raising / lowering control process is executed by the CPU 60, first, as shown in FIG.

In step S100, the vision processor 72 captures an image, and in step S102, a feature point of a staircase is extracted by a light cutting method based on the captured image.
FIG. 8 is a diagram for explaining the principle of the light cutting method.
The light section method is a measurement method for obtaining coordinates on a measurement object based on the principle of triangulation. FIG. 8 shows a measurement coordinate system.

  The coordinates P (x0, y0, z0) on the measurement target are obtained by the following equation (1), where arbitrary coordinates on the image sensor of the camera 32 are Ps (xi, yi, zi).

Next, from the obtained three-dimensional coordinates, a discontinuous point or a bent point of the reflected light of the laser beam is extracted as a feature point of the staircase.
FIG. 9 is a diagram illustrating a state in which the staircase is irradiated with laser light and an image of the imaging element of the camera 32.

  When a stairway is present on the movement path of the leg-wheel type robot 100, as shown on the left side of FIG. 9A, the horizontal laser light emitted from the horizontal laser 26 is reflected by the kick plate and the floor surface of the staircase, and the camera 32. Thus, an image of the stairs including the reflected light is taken. When image processing is performed on the image, as shown on the right side of FIG. 9A, the reflected light edge on the kick plate and the reflected light edge on the floor surface can be extracted. Based on the edge image and the three-dimensional coordinates obtained by the above equation (1), the actual coordinates corresponding to the discontinuous points of the reflected light edge can be calculated.

  Further, as shown on the left side of FIG. 9B, the vertical plane laser light emitted from the vertical laser 28 is reflected by the stair riser plate and the step board, and the camera 32 captures an image of the staircase including the reflected light. The When image processing is performed on the image, a reflected light edge on the kick board and a reflected light edge on the tread board can be extracted as shown on the right side of FIG. The same applies to the vertical laser 30. As shown on the right side of FIG. 9C, the reflected light edge on the kick board and the reflected light edge on the tread board can be extracted. Based on these edge images and the three-dimensional coordinates obtained by the above equation (1), the actual coordinates with respect to the bending point of the reflected light edge can be calculated.

Returning to FIG. 7, the process then proceeds to step S <b> 104, where the width of the staircase is calculated based on the extracted feature points, and the process proceeds to step S <b> 106, where the actual coordinates of the stair nosing part of the staircase are calculated. Then, the process proceeds to step S108.
In step S108, a motor command signal is output to the driver of the motor 82 to rotate the in-plane scanning leg tip sensor 38, the process proceeds to step S110, and a sensor signal is input from the in-plane scanning leg tip sensor 38, step S112. If it is determined whether or not sensor signals measured at a plurality of different rotation angles are input, and it is determined that sensor signals at a plurality of rotation angles are input (Yes), the process proceeds to step S114.

FIG. 10 is a diagram showing a case where a two-dimensional shape measurement is performed by the in-plane scanning leg tip sensor 38.
When the in-plane scanning leg tip sensor 38 is rotated and measurement is performed at a plurality of rotation angles θ _{1 to} θ _i (i = 2, 3,..., N), as shown in FIG. Different distances L _{1 to} L _i to the obstacle can be obtained at 38 at different positions or angles relative to the obstacle. Accordingly, the two-dimensional shape of the obstacle can be measured based on the rotation angles θ _{1 to} θ _i , the distances L _{1 to} L _i, and the position of the in-plane scanning leg tip sensor 38 or the leg 12.

FIG. 11 is a diagram showing a coordinate system and a global (world) coordinate system of the in-plane scanning leg tip sensor 38.
In step S114, a coordinate conversion process for converting the coordinates of the in-plane scanning leg tip sensor 38 into the global coordinate system is performed. In the coordinate conversion process, as shown in FIG. 11, the rotation joints 14 to 18 are J _{0 to} J ₂ , the rotation angles of the rotation joints 14 to 18 are θ ₀ to θ ₂ , and the length of the link between the rotation joints 14 and 16. L ₀ , the length of the link between the rotary joints 16 and 18 is l ₁ , the length of the link between the rotary joint 18 and the leg tip is l ₂ , and from the rotary joint 18 to the in-plane scanning leg tip sensor 38 length of l _s, the length L between the base of the front and rear legs 12, W the length between the base of the left and right legs 12, the global coordinates of the leg-wheeled robot 100 center X _c, Y _c , Z _c , and the posture (roll angle, pitch angle, yaw angle) of the leg wheel type robot 100 is φ, θ, ψ, and the coordinate system Σx _s y _s of the in-plane scanning leg tip sensor 38 according to the following equation (2): measurement points in z _s a _{(x 's, 0, z} ' s), the measurement point in the global coordinate system _{ΣXYZ (X s, Y s,} Z s) in Convert.

  Next, in step S116, inverse kinematics calculation and centroid calculation are performed based on the calculated stair width and the actual coordinates of the nose portion, the sensor signal of the triaxial posture sensor 70, and the result of the coordinate conversion processing in step S114. The process proceeds to S118, where the landing position of the leg tip (drive wheel 20) is determined based on the calculation result in step S116, and the process proceeds to step S120.

In steps S119 to S121, the in-plane scanning leg tip sensor 38 is rotated and measured again. In step S122, the distance to the kick board is calculated. In step S124, the positional relationship between the leg tip and the tread board is calculated. The process proceeds to S126.
In step S126, a motor command signal to the drivers 44 and 54 is generated based on the determined landing position and the calculated both distances. The process proceeds to step S128, and the generated motor command signal is output to the drivers 44 and 54. The process proceeds to step S130.

In step S130, it is determined whether or not the leg tip has landed on the tread. If it is determined that the leg tip has landed (Yes), the series of processes is terminated and the process returns to the original process.
On the other hand, when it is determined in step S130 that the leg tip does not land (No), the process proceeds to step S120.
Next, the operation of the present embodiment will be described.

  If there are stairs on the moving path of the leg-wheel type robot 100, the horizontal plane laser light emitted from the horizontal laser 26 and the vertical plane laser lights emitted from the vertical lasers 28 and 30 are reflected by the stairs, and are reflected by the camera 32. Then, an image including the reflected light is taken. Next, through steps S100 and S102, an image captured by the camera 32 is captured, and feature points of stairs are extracted from the captured image. Then, through steps S104 and S106, the width of the staircase and the actual coordinates of the stair nose are calculated based on the extracted feature points.

  Further, a motor command signal is output to rotate the motor 82, and the in-plane scanning leg tip sensor 38 is rotated by the rotation. At this time, since the angle formed by the measurement direction of the in-plane scanning leg tip sensor 38 with respect to the extending direction of the leg portion 12 changes, the measurement can be performed from a different position or angle with respect to the obstacle. Then, through steps S108 to S114, sensor signals measured at a plurality of rotation angles are input, and the coordinates of the coordinate system of the in-plane scanning leg tip sensor 38 are converted to the global coordinate system.

Then, through steps S116 and S118, the landing position of the leg tip is determined based on the calculated width of the staircase, the actual coordinates of the stair nose, and the conversion result of the coordinate conversion process.
Further, through steps S120 to S124, a sensor signal is input again from the in-plane scanning leg tip sensor 38, and the distance to the kick plate and the positional relationship between the leg tip and the tread board are calculated. Then, through steps S126 and S128, a motor command signal is generated based on the determined landing position and the calculated both distances, and the generated motor command signal is output to the drivers 44 and 54. As a result, the driving wheel 20 rotates and the rotary joints 14 to 18 are driven, and the leg-wheel type robot 100 gets over the stairs while keeping its posture properly. Depending on the situation, the stairs are avoided and stopped. Therefore, the adaptability to the stairs is high like the legged robot.

Moreover, on a flat ground, it can move by wheel drive. Therefore, the mobility on a flat ground is high like the wheel type.
Thus, in the present embodiment, the in-plane scanning leg tip sensor 38 that is rotatably provided on the leg 12 so that the angle formed by the measurement direction with respect to the extending direction of the leg 12 changes, And a motor 82 for rotating the in-plane scanning leg tip sensor 38, and recognizes an obstacle based on the measurement results measured at different rotation angles by the in-plane scanning leg tip sensor 38.

  Thereby, since the in-plane scanning leg tip sensor 38 is provided on the leg portion 12, the interference with the leg portion 12 can be reduced to detect an obstacle, and the in-plane scanning leg tip sensor 38 is used. Since the unknown obstacle is recognized, high adaptability to the unknown obstacle can be realized. Furthermore, since the obstacle is recognized based on the measurement results measured at different rotation angles by the in-plane scanning leg tip sensor 38, the two-dimensional shape of the obstacle can be recognized.

Further, in the present embodiment, the in-plane scanning leg tip sensor 38 is provided at the most distal link of the leg portion 12.
Thereby, the interference of the leg part 12 can be further reduced and an obstacle can be detected.
Furthermore, in the present embodiment, after completion of measurement by the in-plane scanning leg tip sensor 38, drive control of the joint motor 40 is started, and drive control is performed based on the recognition result of the obstacle.

Thereby, since the raising / lowering control of the leg part 12 is performed while recognizing an unknown obstacle using the in-plane scanning leg tip sensor 38, high adaptability to the unknown obstacle can be realized.
Further, in the present embodiment, an image sensor including the lasers 26 to 30 and the camera 32 is provided, the staircase is recognized based on the image photographed by the camera 32, and the joint motor 40 is controlled based on the recognition result.

Thereby, since the raising / lowering control of the leg part 12 is performed while recognizing an unknown staircase using an image sensor, high adaptability with respect to the unknown staircase can be realized. In addition, since it can operate in an environment where people are active, it is suitable for home robots, personal robots, and the like that are used for acting with people.
Further, in the present embodiment, the image sensor is provided on the front surface of the substrate 10, and the in-plane scanning leg tip sensor 38 is provided on the leg portion 12.

This makes it possible to detect an obstacle present on the movement path of the leg wheel type robot 100 with a wide field of view and to accurately measure the distance between the drive wheel 20 and the stairs when the stairs are raised and lowered.
Furthermore, in this embodiment, the lasers 26 to 30 that irradiate the laser beam at a predetermined angle with respect to the moving direction, and an image that is provided at a predetermined distance from the lasers 26 to 30 and includes the reflected light of the laser beam are captured. The camera 32 is provided, and the staircase is recognized by the light cutting method based on the image photographed by the camera 32.

Thereby, since the characteristic effective for the raising / lowering control of the leg part 12 can be detected among the characteristics of the staircase, higher adaptability can be realized for the unknown staircase.
Furthermore, in the present embodiment, the width of the staircase is calculated based on the imaging state of the reflected light of the horizontal plane laser light emitted from the horizontal laser 26, and the two vertical surface laser lights emitted from the vertical lasers 28 and 30 are calculated. The actual coordinates of the stair nosing part of the staircase are calculated based on the reflected light imaging state.

Thereby, since the characteristic more effective for the raising / lowering control of the leg part 12 can be detected among the characteristics of the staircase, higher adaptability can be realized for the unknown staircase.
Further, in the present embodiment, the positional relationship between the drive wheel 20 and the stair kick plate and the tread plate is calculated based on the measurement result of the in-plane scanning leg tip sensor 38.
Thereby, since the characteristic more effective for the raising / lowering control of the leg part 12 can be detected among the characteristics of the staircase, higher adaptability can be realized for the unknown staircase.

  In the first embodiment, the in-plane scanning leg tip sensor 38 corresponds to the distance measuring sensor of the invention 1 to 5 or 7, and the motor 82 corresponds to the actuator of the invention 1, 3 or 4, and step S108. S118 corresponds to the obstacle recognition means of the invention 1 or 5, and the joint motor 40 corresponds to the second actuator of the invention 5. Steps S126 and S128 correspond to the control means of the fifth aspect.

[Second Embodiment]
Next, a second embodiment of the present invention will be described with reference to the drawings. 18 to 22 are views showing a second embodiment of the leg-wheel type robot according to the present invention.

In addition to the functions of the leg wheel type robot 100 of the first embodiment, the leg wheel type robot 100 of the present embodiment has the leg wheel type robot 100 in a state where the orientation of the base body 10 is held in a fixed direction. It has a function of running and moving in an arbitrary traveling direction, and a function of turning the leg-wheel type robot 100 without moving back and forth at a predetermined turning center position (turning in a superficial position).
That is, the leg wheel type robot 100 according to the present embodiment is provided with an installation structure of the force sensor 82 only by adding an actuator control process (control process by executing a control program of the CPU 60) for realizing the above functions. Other configurations are the same as those of the leg-wheel type robot 100 of the first embodiment. Therefore, description of functions similar to those of the first embodiment will be omitted as appropriate, and added functional parts will be described in detail.

Hereinafter, based on FIGS. 18-20, the control process at the time of the travel movement performed by CPU60 of this Embodiment is demonstrated.
Here, FIGS. 18A and 18B are views showing the posture of the leg-wheel type robot 100 when traveling on wheels.
In each of the following travel control processes, each joint motor 40 is controlled so that the posture of the leg-wheel type robot 100 becomes a knee flexion posture as shown in FIG. However, when the leg portions 12 interfere with each other (contact or the like) during running control in the knee flexion posture, the joint motors 40 are controlled so as to be in the knee extension posture as shown in FIG.

First, a travel control process (hereinafter referred to as a non-directed travel control process) when the leg-wheel type robot 100 travels in a desired traveling direction with the orientation of the base body 10 held (fixed) in a certain direction. ).
The CPU 60 activates a control program stored in a predetermined area such as a ROM, and executes a non-turning traveling control process according to the control program.

  Here, the non-turning traveling control process moves the leg-wheel type robot 100 in the target traveling direction while keeping the direction of the base body 10 in a fixed direction. It is desirable to provide the camera 32, the obstacle sensors 34, 36, and the like provided on the rear side and the side. When the leg-wheel type robot 100 is moved in a direction different from the direction of the base body 10 by the camera and the obstacle sensor that can cover the rear side and the side, the environment (the terrain state, etc.) in the traveling direction is grasped. Appropriate control can be performed.

Further, the non-turning traveling control process is executed when there is a non-turning traveling control command, and the robot traveling direction (angle α) and the robot traveling direction speed Vc are input as the input. The angle (steering angle) of the rotary joint 14 (joint0) of each leg 12 for causing the leg-wheel type robot 100 to travel in the input traveling direction while maintaining the orientation of the base body 10 in a certain direction. θ _i0 (i = 0,1,2,3,...), and the rotational angular velocity ω _i (i = 0,1,2,3,...) of each drive wheel 20 of each leg 12 are calculated. A command is given to each actuator.

As described in the first embodiment, the leg-wheel type robot 100 according to the present embodiment has a total of four leg portions 12 in a pair of left and right in the front of the base 10 and a pair of left and right in the rear. .
Therefore, here, the steering angle θ _i0 of the driving wheel 20 of each leg 12 is viewed from the upper surface side of the base 10, the left front wheel steering angle θ ₀₀ , the right front wheel steering angle θ ₁₀ , and the left rear wheel steering angle θ _20. The right rear wheel steering angle θ ₃₀ is set. Incidentally, the rotation joint 14 when rotated each leg 12 about the yaw axis, as viewed from the top side of the base body 10, a left front-wheel steering angle theta ₀₀ and the right rear wheel steer angle theta ₃₀ is counterclockwise The direction is a positive direction, and the right front wheel steering angle θ ₁₀ and the left rear wheel steering angle θ ₂₀ are clockwise directions.

Further, the rotational angular velocities ω _i of the drive wheels 20 of the respective leg portions 12 are defined as a left front wheel rotational angular velocity ω ₀ , a right front wheel rotational angular velocity ω ₁ , a left rear wheel rotational angular velocity ω ₂ , and a right rear wheel rotational angular velocity ω ₃ .
Further, the linear velocity V _i (i = 0, 1, 2, 3,...) Of the driving wheel 20 of each leg 12 is set to the left front wheel linear velocity V ₀ , the right front wheel linear velocity V ₁ , and the left rear wheel lane. A speed V ₂ and a right rear wheel linear speed V ₃ are used.
Here, FIGS. 19A to 19C are diagrams illustrating an example of the traveling state of the leg-wheel type robot 100 during the non-turning traveling control. FIGS. 19A to 19C are views of the leg wheel type robot 100 as viewed from the upper surface side, and the black semicircle mark attached to each drive wheel 20 is “θ ₀₀ = θ ₁₀ = θ ₂₀ = θ ₃₀ = 0 [°] ”indicates a reference direction.

In addition, the rotation direction of the left and right front wheels traveling in the direction with the mark is the positive rotation direction, and the rotation direction of the left and right rear wheels traveling in the direction without the mark is the positive rotation direction.
First, based on FIG. 19A, when the leg-wheel type robot 100 is made to travel straight in the direction (forward direction) in which the base body 10 is facing with the orientation of the base body 10 being held (fixed) in a certain direction. The non-turning traveling control process will be described.

In the present embodiment, when the direction in which the base body 10 is facing (forward direction) is the traveling direction of the robot, the angle α representing the traveling direction is set to “0 [°]”. Then, α corresponding to each traveling direction is determined with reference to 0 [°] in the forward direction.
Here, since the leg wheel type robot 100 is caused to advance straight forward of the base body 10, “0 [°]” is input as the traveling direction α, and the traveling direction speed Vc is further input.

When the traveling direction α (0 [°]) and the traveling direction speed Vc are input, the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ of each driving wheel 20 and the linear speed V ₀ of each driving wheel 20 V ₁ , V ₂ and V ₃ are calculated.
In order to cause the leg wheel type robot 100 to travel straight forward while maintaining the orientation of the base body 10, as shown by the arrows extending from the drive wheels 20 in FIG. It is necessary to align all the traveling directions in the direction in which the base body 10 is facing (forward direction). Accordingly, the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , and θ ₃₀ are calculated as, for example, “θ ₀₀ = θ ₁₀ = θ ₂₀ = θ ₃₀ = 0 [°]”.

Further, in this case, the linear velocities V ₀ , V ₁ , V ₂ , and V ₃ of the drive wheels 20 for running straight ahead are “V ₀ = V ₁ = Vc” and “V ₂ = V ₃ = −Vc”. Is calculated.
If the legs 12 do not interfere with each other, for example, “θ ₀₀ = θ ₁₀ = 0 [°]”, “θ ₂₀ = θ ₃₀ = π (180 [°])” or −π (−180 [° ]) ”,“ V ₀ = V ₁ = V ₂ = V ₃ = Vc ”, etc.

Further, the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are converted into rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ according to the following equation (3).

ω _i = 2V _i / D (3)

However, in the above formula (3), D is a wheel diameter.

Once the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ and the rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω _{3 of the} drive wheels 20 are calculated, 20 current steering angles and rotational angular velocities are obtained. Then, a command value for driving the joint motor 40 of the rotary joint 14 is calculated from the current steering angle and the calculated steering angle for moving straight forward. Further, a command value for driving the wheel motor 50 of the drive wheel 20 is calculated from the current rotation angular velocity and the rotation angular velocity when the vehicle travels straight in the forward direction.

  When the steering control command value and the speed control command value of each drive wheel 20 are calculated in this way, these command values are input to the drivers of the motors. Then, when each joint motor 40 and wheel motor 50 are driven based on the input command value, the steering angle and the rotational angular velocity of each drive wheel 20 of the leg wheel type robot 100 are thereby changed, and the leg wheel type robot is changed. In a state where the orientation of the base body 10 is maintained, the vehicle 100 travels straight in the facing direction (forward direction).

In the case where the leg-wheel type robot 100 is caused to travel straight in the direction opposite to the direction in which the base wheel type robot 100 is directed (directly rearward) with the base 10 kept in a certain direction, What is necessary is just to make the rotation direction of the driving wheel 20 opposite.
For example, “θ ₀₀ = θ ₁₀ = θ ₂₀ = θ ₃₀ = 0 [°]” and “V ₀ = V ₁ = V ₂ = V ₃ = −Vc” or “θ ₀₀ = θ ₁₀ = 0 [°] “Θ ₂₀ = θ ₃₀ = π or −π [°]”, “V ₀ = V ₁ = −Vc”, “V ₂ = V ₃ = Vc”, and the like.

Next, based on FIG. 19B, with the orientation of the base body 10 maintained (ie, with the front facing forward), the leg wheel type robot 100 is tilted forward to the right with respect to the direction it is facing. Next, the non-turning traveling control process when traveling straight ahead will be described.
Here, since the leg-wheel type robot 100 moves straight forward in the diagonally right direction of the base body 10, the traveling direction α is “α (−90 <α <0) [°] (where counterclockwise is the positive direction)”. Is input, and the traveling direction speed Vc is further input.

When the traveling direction α [°] and the traveling direction speed Vc are input, the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ of each driving wheel 20 and the linear speeds V ₀ , V of each driving wheel 20 are input. ₁ , V ₂ and V ₃ are calculated.
In order to cause the leg wheel type robot 100 to travel straight ahead in the diagonally right direction (α [°] direction) while maintaining the orientation of the base body 10, the arrows extending from the drive wheels 20 in FIG. As shown, it is necessary to align all the traveling directions of the drive wheels 20 in the diagonally forward right direction with respect to the direction in which the base body 10 is directed.

Therefore, the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ are calculated as, for example, “θ ₀₀ = θ ₃₀ = α [°]”, “θ ₁₀ = θ ₂₀ = −α [°]”.
Further, in this case, the linear velocities V ₀ , V ₁ , V ₂ , and V ₃ of the drive wheels 20 for running straight ahead are “V ₀ = V ₁ = Vc” and “V ₂ = V ₃ = −Vc”. Is calculated.
If the legs 12 do not interfere with each other, for example, “θ ₀₀ = θ ₃₀ = α [°]”, “θ ₁₀ = θ ₂₀ = −α−π [°]”, “V ₀ = V ₂ = Vc ", may be as a combination, such as" V ₁ = V ₃ = -Vc ".

Further, the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are converted into rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ according to the above equation (3).
When the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ and the rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω _{3 of the} respective drive wheels 20 are calculated, next, the straight traveling in the forward direction is performed. Similarly, the command value for driving the joint motor 40 of the rotary joint 14 and the command value for driving the wheel motor 50 of the drive wheel 20 are calculated.

  When the steering control command value and the speed control command value of each drive wheel 20 are calculated in this way, these command values are input to the drivers of the motors. Then, when each joint motor 40 and wheel motor 50 are driven based on the input command value, the steering angle and the rotational angular velocity of each drive wheel 20 of the leg wheel type robot 100 are thereby changed, and the leg wheel type robot is changed. In a state where the orientation of the base body 10 is maintained, the vehicle 100 travels straight forward in a diagonally forward right direction with respect to the facing direction.

  When the leg-wheel type robot 100 travels straight diagonally to the left and backward with respect to the direction in which the base body 10 is held, each drive wheel 20 in the right diagonal forward direction is used. What is necessary is just to make the rotation direction opposite. Further, when moving straight ahead in the diagonally left direction, the traveling direction α may be set in a range of “0 <α <90 [°]”, and the sign of the steering angle may be opposite. Further, in the case where the vehicle travels straight diagonally to the right, the rotational direction of each drive wheel 20 in the diagonally forward left direction may be opposite to that of the front.

Next, based on FIG. 19 (c), the non-turning traveling control in the case where the leg-wheel type robot 100 travels straight in the left lateral direction with respect to the direction in which the base body 10 is maintained. Processing will be described.
Here, since the leg-wheel type robot 100 is moved straight in the left lateral direction of the base body 10, “α (90 (π / 2)) [°]” is input as the traveling direction α, and the traveling direction velocity Vc is Entered.

When the traveling direction α [°] and the traveling direction speed Vc are input, the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ of each driving wheel 20 and the linear speeds V ₀ , V of each driving wheel 20 are input. ₁ , V ₂ and V ₃ are calculated.
In order to cause the leg wheel type robot 100 to travel straight in the left lateral direction (direction of π / 2 [°]) with respect to the direction in which the base body 10 is maintained, FIG. ), It is necessary to align all the traveling directions of the driving wheels 20 in the left lateral direction.

Accordingly, the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ are calculated as, for example, “θ ₀₀ = θ ₁₀ = θ ₂₀ = θ ₃₀ = π / 2 [°]”.
In this case, the linear velocities V ₀ , V ₁ , V ₂ , and V ₃ of the drive wheels 20 for running straight ahead are “V ₀ = V ₂ = Vc” and “V ₁ = V ₃ = −Vc”. Is calculated.
If the legs 12 do not interfere with each other, for example, “θ ₀₀ = θ ₂₀ = π / 2 [°]”, “θ ₁₀ = θ ₃₀ = −π / 2 [°]”, “V ₀ = A combination such as “V ₁ = V ₂ = V ₃ = Vc” may be adopted.

Further, the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are converted into rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ according to the above equation (3).
When the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ and the rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω _{3 of the} respective drive wheels 20 are calculated, next, the straight traveling in the forward direction is performed. Similarly, the command value for driving the joint motor 40 of the rotary joint 14 and the command value for driving the wheel motor 50 of the drive wheel 20 are calculated.

  When the steering control command value and the speed control command value of each drive wheel 20 are calculated in this way, these command values are input to the drivers of the motors. Then, when each joint motor 40 and wheel motor 50 are driven based on the input command value, the steering angle and the rotational angular velocity of each drive wheel 20 of the leg wheel type robot 100 are thereby changed, and the leg wheel type robot is changed. In a state in which the orientation of the base body 10 is maintained, the vehicle 100 travels straight in the left lateral direction with respect to the facing direction.

When the leg-wheel type robot 100 travels straight in the right lateral direction with respect to the direction in which the base body 10 is held, the rotation of each driving wheel 20 in the left lateral direction is performed. The direction may be opposite.
Next, a travel control process for turning the leg wheel type robot 100 without moving back and forth at a predetermined turning center position (hereinafter, referred to as super-trust turning control process) will be described.

The CPU 60 activates a control program stored in a predetermined area such as a ROM, and executes super turning control processing according to the control program.
Here, the super-revolution turning control process causes the leg wheel type robot 100 to perform a turn operation equivalent to super-revolution performed by a vehicle such as a power shovel or a tank having a crawler mechanism.
In addition, super turning is a turning method in which a vehicle having a crawler mechanism rotates left and right crawlers in the opposite directions at the same speed so that the vehicle body does not move forward and backward and the direction of the vehicle body changes. This is a turning method that can be realized not only in the crawler mechanism but also in a vehicle having at least two independent drive wheels on the left and right.

In the present embodiment, specifically, it is executed when there is a super turning control command, and the turning angular velocity Ω of the robot and the turning center (xc, yc) are used as inputs to turn the leg wheel type robot 100 into the turning center. Angles (steering angles) θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ of the rotary joints 14 (joint 0) of the respective leg portions 12 for driving each of the leg portions 12 in order to make a super turn at (xc, yc) The rotational angular velocities ω ₀ , ω ₁ , ω ₂ , and ω ₃ of the wheel 20 are calculated, and commands are given to each actuator.

  In order to cause the leg wheel type robot 100 to make a super turn, when the base body 10 is rotated about the yaw axis at the turning center (xc, yc), the rotation about the yaw axis at the time of steering of each drive wheel 20 is performed. The joint motor 40 of each rotary joint 14 is controlled so that the direction of movement at the contact point between the arc trajectory drawn by the center and the rotation center of each drive wheel 20 matches the traveling direction of each drive wheel 20, and each drive It is necessary to control each wheel motor 50 so that the wheel 20 rotates at a constant speed in the rotation direction corresponding to the movement direction.

Here, FIGS. 20 (a) and 20 (b) show the leg-wheel type robot 100 at the time of super-superior turning control with the coordinates (0, 0) and the coordinates (xc, yc) of the base body 10 as the rotation center. It is a figure which shows a driving | running | working state.
20 (a) and 20 (b), in the plane when the base body 10 is viewed from the upper surface side, the longitudinal axis is the x-axis and the direction perpendicular thereto is the y-axis. The coordinates are (x, y) = (0, 0).

First, based on FIG. 20 (a), a description will be given of super turning control processing in the case where the coordinate (0, 0) of the center position of the base body 10 is set as the turning center.
In this case, the turning angular velocity Ω and the turning center coordinates (0, 0) are input.
When the turning angular velocity Ω and the turning center coordinates (0, 0) are input, the angles φ ₀ , φ ₁ , φ formed by the x axis of the base 10 and the rotation center of each drive wheel 20 based on the following equation (4). _2, phi ₃ is calculated.

tan φ = W _t / W _b (4)

However, the above equation (4) is an equation in the case where the center coordinate (0, 0) of the base 10 is set as the turning center. In the above equation (4), W _t is a tread (wheel spacing), and W _b is a wheel base.

Note that φ _{0 to} φ ₃ are the minimum angles among the angles formed between the x-axis and the rotation center of each drive wheel 20, and the positive direction of φ differs from the positive direction of Ω depending on the drive wheels.
Since W _t and W _b are known (information is stored in advance), the above angles φ ₀ , φ ₁ , φ ₂ , and φ ₃ can be calculated from the above equation (4).
Since the turning center is the center coordinate (0, 0) of the base body 10, the angles φ ₀ , φ ₁ , φ ₂ , and φ ₃ are all equal angles “φ ₀ = φ ₁ = φ ₂ = φ ₃ = φ. "

In addition, when the base body 10 rotates around the yaw axis at the turning coordinates (0, 0), the movement direction at the contact point between the circular arc drawn by the rotation center around the yaw axis and the rotation center at the time of steering of each drive wheel 20 is: As indicated by the arrow lines extending from each drive wheel 20 in FIG. 20A, the direction is a tangential direction (in the direction of the arrow line in the figure) passing through each rotation center on the circular arc track.
Once the angle “φ ₀ = φ ₁ = φ ₂ = φ ₃ = φ” with respect to the rotation center of each drive wheel 20 is calculated, the movement direction of each rotation center and the traveling direction of each drive wheel 20 are matched. Steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , and θ ₃₀ are calculated.

In order to make the movement direction of each rotation center coincide with the traveling direction of each driving wheel 20, as shown in FIG. 20A, a line connecting the traveling direction of each driving wheel 20, the turning center and the rotation center. It is only necessary to perform steering so that the angle formed by the minute is a right angle (π / 2 (90 [°])). Therefore, the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , and θ ₃₀ are “θ ₀₀ = θ ₁₀ = Θ ₂₀ = θ ₃₀ = − (π / 2−φ) ”.
On the other hand, the distances L ₀ , L ₁ , L ₂ , L ₃ between the rotation center around the yaw axis and the turning center (0, 0) during steering of each drive wheel 20 are calculated based on the following equation (5). .

However, the above equation (5) is an equation in the case where the center coordinate (0, 0) of the base body 10 is set as the turning center.
From the tread W _t and the wheel base W _b , the coordinates of the rotation center of the left front wheel are (W _b / 2, W _t / 2), and the coordinates of the rotation center of the right front wheel are (W _b / 2, −W _t / 2) The coordinates of the center of rotation of the left rear wheel are represented as (−W _b / 2, W _t / 2), and the coordinates of the center of rotation of the right rear wheel are represented as (−W _b / 2, −W _t / 2). Can do.

Since the turning center is the center coordinate (0, 0) of the base body 10, the distances L ₀ , L ₁ , L ₂ , L ₃ are equal distances “L ₀ = L ₁ = L ₂ = L ₃ = L”. It becomes.
Once the distances L ₀ , L ₁ , L ₂ , L ₃ are calculated, the linear velocities V ₀ , V ₀ of each drive wheel 20 are then calculated from these distances L and the turning angular velocity Ω based on the following equation (6). V ₁ , V ₂ and V ₃ are calculated.

V ₀ = V ₁ = V ₂ = V ₃ = LΩ (6)

However, the above expression (6) is an expression when the center coordinates (0, 0) of the base body 10 are set as the turning center.

Here, as described above, the rotation direction of the left and right front wheels traveling in the direction with the black semicircle mark is the positive rotation direction, and the rotation direction of the left and right rear wheels traveling in the direction without the mark is the positive rotation direction.
Further, since the directions of the drive wheels 20 are as shown in FIG. 20A, the linear velocities V ₀ , V ₁ , V ₂ , and V ₃ are “V ₀ = V ₃ = −LΩ”, “V ₁ = V ₂ = LΩ ”is calculated.
Further, the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are converted into rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ according to the above equation (3).

Once the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ and the rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ of each drive wheel 20 are calculated, the current steering of each drive wheel 20 is then performed. Get the angle and rotational angular velocity. Then, a command value for driving the joint motor 40 of the rotary joint 14 is calculated from the current steering angle and the calculated steering angle. Further, a command value for driving the wheel motor 50 of the drive wheel 20 is calculated from the current rotation angular velocity and the calculated rotation angular velocity.

  When the steering control command value and the speed control command value of each drive wheel 20 are calculated in this way, these command values are input to the drivers of the motors. Then, when each joint motor 40 and wheel motor 50 are driven based on the input command value, the steering angle and the rotational angular velocity of each drive wheel 20 of the leg wheel type robot 100 are thereby changed, and the center of the base body 10 is changed. With the coordinates (0, 0) as the turning center, the leg-wheel type robot 100 turns on the spot without making a back-and-forth movement.

Next, the super turning control process when coordinates other than the center coordinate (0, 0) of the base 10 are set as the turning center will be described. Hereinafter, this super turning control process is referred to as a turning center offset type super turning control process.
In this case, the turning angular velocity Ω and turning center coordinates (xc, yc) ≠ (0, 0) which are coordinates other than the center coordinates (0, 0) of the base body 10 are input.

Then, when the turning angular velocity Ω and the turning center coordinates (xc, yc) are input, the angles φ ₀ , φ ₁ formed by the x axis of the base 10 and the rotation center of each drive wheel 20 based on the following equation (7). , Φ ₂ , φ ₃ are calculated.

tan φ ₀ = (W _t / 2-yc) / (W _b / 2-xc)
tan φ ₁ = (W _t / 2 + yc) / (W _b / 2-xc)
tanφ ₂ = (W _t / 2-yc) / (W _b / 2 + xc)
tan φ ₃ = (W _t / 2 + yc) / (W _b / 2 + xc) (7)

However, the above equation (7) is an equation in the case where there are a total of four leg portions 12 of the leg-wheel type robot 100, that is, a pair of left and right in front of the base body 10 and a pair of left and right in the rear.

Specifically, the input turning center coordinates (xc, yc) and known W _t and W _b are substituted into the above equation (7), and the x axis of the base 10 and the rotation center of each drive wheel 20 are substituted. Are calculated. Φ ₀ , φ ₁ , φ ₂ , φ ₃ are calculated.
Since the turning center is a coordinate other than the center coordinate of the base body 10, the angles φ ₀ , φ ₁ , φ ₂ , and φ ₃ are different from each other.

  Further, when the base body 10 rotates around the yaw axis at the turning center coordinates (xc, yc), the direction of motion at the contact point between the circular arc drawn by the rotation center around the yaw axis and the rotation center at the time of steering of each drive wheel 20. As shown by the arrow lines extending from the drive wheels 20 in FIG. 20 (b), they are tangential directions (in the direction of the arrow lines in the figure) passing through the rotation centers on the circular arc tracks. Further, since the distance between the turning center and the rotation center of each drive wheel 20 is different, the arc trajectory drawn by each rotation center is also different.

Once the angles φ ₀ , φ ₁ , φ ₂ , and φ ₃ with respect to the rotation center of each drive wheel 20 are calculated, next, steering for making the movement direction of each rotation wheel coincide with the traveling direction of each drive wheel 20. The angles θ ₀₀ , θ ₁₀ , θ ₂₀ , and θ ₃₀ are calculated.
In order to make the movement direction of each rotation center coincide with the traveling direction of each drive wheel 20, as shown in FIG. 20B, a line connecting the rotation direction of each drive wheel 20, the turning center and the rotation center. It is only necessary to steer so that the angle formed by the minute becomes a right angle (π / 2 (90 [°])). Therefore, the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , and θ ₃₀ are “θ _i0 = − ( π / 2-φ _i) is calculated as (i = 0, 1, 2, 3) ".

On the other hand, the distances L ₀ , L ₁ , L ₂ , L ₃ between the rotation center around the yaw axis and the turning center (xc, yc) during the steering of each drive wheel 20 are calculated based on the following equation (8). .

As described above, since the turning center is a coordinate other than the center coordinates (0, 0) of the base body 10, the distances L ₀ , L ₁ , L ₂ , and L ₃ are different distances.
Once the distances L ₀ , L ₁ , L ₂ , L ₃ are calculated, the linear velocities V ₀ , V ₀ of the drive wheels 20 are then calculated from these distances and the turning angular velocity Ω based on the following equation (9). ₁ , V ₂ and V ₃ are calculated.

| V _i | = | L _i Ω | (9)

Therefore, the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are “V ₀ = −L ₀ Ω”, “V ₁ = L ₁ Ω”, “V ₂ = L ₂ Ω”, “V ₃ = − L ₃ Ω ”.

Further, the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are converted into rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ according to the above equation (3).
Once the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ and the rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ of each drive wheel 20 are calculated, the current steering of each drive wheel 20 is then performed. Get the angle and rotational angular velocity. Then, a command value for driving the joint motor 40 of the rotary joint 14 is calculated from the current steering angle and the calculated steering angle. Further, a command value for driving the wheel motor 50 of the drive wheel 20 is calculated from the current rotation angular velocity and the calculated rotation angular velocity.

  When the steering control command value and the speed control command value of each drive wheel 20 are calculated in this way, these command values are input to the drivers of the motors. Then, when each joint motor 40 and wheel motor 50 are driven based on the input command value, the steering angle and the rotational angular velocity of each drive wheel 20 of the leg wheel type robot 100 are thereby changed. With the coordinates (xc, yc) other than the position (0, 0) as the turning center, the leg-wheel robot 100 turns (super turning) without moving back and forth.

Next, based on FIG.21 and FIG.22, operation | movement of this Embodiment is demonstrated.
Here, FIGS. 21A and 21B are diagrams illustrating an example of a travel route of the leg-wheel type robot 100. FIG. FIG. 22 is a diagram illustrating an example of the position of the center of gravity of the robot.
When the leg-wheel type robot 100 determines that there is no obstacle on its own movement path based on the sensor signals of the obstacle sensors 34 and 36 and the in-plane leg tip sensor 38 (is a flat ground), the movement mode Is switched from the leg movement mode using the leg 12 to the wheel traveling movement mode using the drive wheels 20.

On flat ground, the leg-wheel type robot 100 can move in the above-mentioned non-turning traveling. In addition, the above-described super-spinning and turning center offset type super-spinning can be performed.
Further, when the wheels are running and turning, the joint motor 40 is controlled so that the leg wheel type robot 100 is in the knee bending posture.
When the mode is switched to the wheel traveling mode, the leg wheel type robot 100 controls each joint motor 40 of the leg 12 to shift to the knee flexion posture. Thereby, various traveling control is started.

First, the operation of the leg wheel type robot 100 during the non-turning traveling control will be described.
Here, it is assumed that the leg wheel type robot 100 travels and moves along a passage as shown in FIG. FIGS. 21A and 21B are overhead views of the leg wheel type robot 100 as viewed from directly above.
As shown in FIG. 21 (a), the width of the passage is initially narrow enough to pass through in the direction (front direction) in which the base body 10 is facing, so first, before entering the passage, The direction in which the passage extends and the direction of the base 10 are matched, and the entry position and the entry angle are adjusted.

Then, the non-turning traveling control command is input, and the leg wheel type robot 100 is shifted to the non-turning traveling control mode. As a result, the leg wheel type robot 100 controls the CPU 60 to travel and move in the target traveling direction while maintaining the orientation of the base 10.
First, since the leg wheel type robot 100 is desired to move straight forward, the robot traveling direction α = 0 [°] and the robot traveling direction speed Vc are input. Thereby, the steering angle of each drive wheel 20 is calculated as “θ ₀₀ = θ ₁₀ = θ ₂₀ = θ ₃₀ = 0 [°]”, and the linear velocity of each drive wheel 20 is “V ₀ = V ₁ = V _2”. = V ₃ = Vc ”.

Further, the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are converted into rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ according to the above equation (3).
When the CPU 60 calculates the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ , and the rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ of the drive wheels 20, the angle capture I / F 62 is then obtained. The current steering angle and rotational angular velocity of each drive wheel 20 are acquired. Here, a difference value between the acquired steering angle and the calculated steering angle is calculated, and a command value for driving the joint motor 40 of the rotary joint 14 is calculated based on the difference value. Further, a difference value between the acquired current rotation angular velocity and the calculated rotation angular velocity is calculated, and a command value for driving the wheel motor 50 of the drive wheel 20 is calculated based on the difference value.

  The CPU 60 inputs the calculated steering control command value and speed control command value of each drive wheel 20 to the driver of each motor. With this command value, each joint motor 40 is driven, and the rotary joint 14 of each leg 12 rotates about the yaw axis to change to a target steering angle. Thereafter, each wheel motor 50 is driven, and each drive wheel 20 is rotationally driven at a rotational angular velocity corresponding to the command value. As a result, the leg wheel type robot 100 enters the passage in the direction (front direction) in which the base body 10 is facing while keeping the orientation of the base body 10 and travels straight in the passage.

When the leg-wheel type robot 100 moves straight forward for a while, the passage bends to the right at a substantially right angle and further widens the road, so that the base 10 is kept in the right direction with respect to the direction in which the base 10 is held. Control to move straight in the direction. That is, α = −90 (−π / 2) [°] is input as the traveling direction, and further the traveling direction velocity Vc is input.
Thereby, “θ ₀₀ = θ ₁₀ = θ ₂₀ = θ ₃₀ = α [°]” is calculated as the steering angle, and “V ₀ = V ₂ = −Vc”, “V ₁ = V ₃ ” as the linear velocities. = Vc "is calculated.

Further, the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are converted into rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ according to the above equation (3).
The CPU 60 acquires the current steering angle and rotational angular velocity of each drive wheel 20, and calculates each command value from these and the calculated steering angle and rotational angular velocity. By this command value, each joint motor 40 and each wheel motor 50 are driven, so that the leg wheel type robot 100 holds the direction of the base body 10 in the right lateral direction with respect to the direction in which it is directed. Drive straight ahead. Thus, the leg wheel type robot 100 can be caused to travel to the bent point without turning at the corner of the passage.

When the leg-wheel type robot 100 goes straight in the right lateral direction for a while, the passage bends in the diagonally downward right direction, and this time, with the orientation of the base body 10 maintained, this time, in the diagonally backward right direction with respect to the direction in which it is facing. Control to move straight. That is, α (passage angle <0) [°] is input as the traveling direction, and further the traveling direction velocity Vc is input.
Thereby, for example, “θ ₀₀ = θ ₃₀ = π + α [°]” and “θ ₁₀ = θ ₂₀ = − (π + α) [°]” are calculated as the steering angle, and “V ₀ = V “ ₁ = −Vc” and “V ₂ = V ₃ = Vc” are calculated.

Further, the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are converted into rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ according to the above equation (3).
Then, the current steering angle and rotation angular velocity of each drive wheel 20 are acquired, and each command value is calculated from these and the calculated steering angle and rotation angular velocity. By this command value, each joint motor 40 and each wheel motor 50 are driven, so that the leg wheel type robot 100 holds the orientation of the base body 10 in the diagonally rightward direction with respect to the direction in which the base 10 is facing. Go straight ahead.

Next, the operation of the leg wheel type robot 100 at the time of super-trust turning control will be described.
Here, it is assumed that the leg wheel type robot 100 travels and moves along a passage as shown in FIG.
As shown in FIG. 21 (b), the passage extends straight at first, then turns to the right at a substantially right angle, and reaches a dead end after that.

First, the direction in which the passage extends and the direction of the base body 10 are matched and the approach position is finely adjusted, and then the leg-wheel type robot 100 is caused to travel straight ahead in the forward direction. Thereby, the leg-wheel type robot 100 enters the passage and travels straight in the passage.
When the leg wheel type robot 100 goes straight for a while, the leg wheel type robot 100 eventually reaches the turning corner, and therefore turns clockwise to change the direction of the base body 10 so that the leg wheel type robot 100 can advance.

  If it is the corner shown in FIG. 21 (b), it is possible to make a right turn even with a turning motion accompanied by a forward movement, but here it is assumed that a right turn is made by a super turn. For this reason, a super-trust turning control command is input, and the leg wheel type robot 100 is shifted to the super-trust turning control mode by this command. As a result, the leg wheel type robot 100 performs a control process in which the CPU 60 turns the robot at a predetermined turning center position without moving back and forth.

First, a turning angular velocity Ω (an angular velocity for rotating the base body 10 clockwise) and a turning center coordinate (0, 0) are input. Further, since the right turn is performed at a substantially right angle, a turning angle of −90 [°] is input.
When the turning angular velocity Ω, the turning center coordinates (0, 0), and the turning angle (−90 [°]) are input, the x axis of the base 10 and the rotation center of each drive wheel 20 are determined based on the above equation (4). Are calculated. Φ ₀ , φ ₁ , φ ₂ , φ ₃ are calculated.

Once the angle “φ ₀ = φ ₁ = φ ₂ = φ ₃ = φ” with respect to the rotation center of each drive wheel 20 is calculated, the movement direction of each rotation center and the traveling direction of each drive wheel 20 are matched. Steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , and θ ₃₀ are calculated.
Specifically, for the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , and θ ₃₀ , “θ ₀₀ = θ ₁₀ = θ ₂₀ = θ ₃₀ = − (π / 2−φ)” is calculated.

Further, based on the above equation (5), distances L ₀ , L ₁ , L ₂ , L ₃ between the rotation center around the yaw axis and the turning center (0, 0) at the time of steering of each drive wheel 20 are calculated. .
Since the turning center is the center coordinates (0, 0) of the base body 10, the distances L ₀ , L ₁ , L ₂ , L ₃ are equal distances “L ₀ = L ₁ = L ₂ = L ₃ = L”. It becomes.
Next, the linear velocities V ₀ , V ₁ , V ₂ , and V ₃ of the drive wheels 20 are calculated from the distance L and the turning angular velocity Ω based on the above equation (6).

Here, since the leg-wheel type robot 100 is turned clockwise (Ω <0), the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are “V ₁ = V ₂ = LΩ”, “V ₀ = V ₃ = −LΩ ”.
Further, the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are converted into rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ according to the above equation (3).
Once the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ and the rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω _{3 of the} drive wheels 20 are calculated, then, via the angle capture I / F 62. Thus, the current steering angle and rotational angular velocity of each drive wheel 20 are acquired. Here, a difference value between the acquired steering angle and the calculated steering angle is calculated, and a command value for driving the joint motor 40 of the rotary joint 14 is calculated based on the difference value. Further, a difference value between the acquired current rotation angular velocity and the calculated rotation angular velocity is calculated, and a command value for driving the wheel motor 50 of the drive wheel 20 is calculated based on the difference value.

  The CPU 60 inputs the calculated steering control command value and speed control command value of each drive wheel 20 to the driver of each motor. With this command value, each joint motor 40 is driven, and the rotary joint 14 of each leg 12 rotates about the yaw axis to change to a target steering angle. Thereafter, each wheel motor 50 is driven, and each drive wheel 20 is rotationally driven at a rotational angular velocity corresponding to the command value. As a result, the leg-wheel type robot 100 turns 90 [°] clockwise (superficial turning) on the spot without moving back and forth with the center coordinate (0, 0) of the base body 10 as the turning center.

When the leg wheel type robot 100 turns 90 [°] clockwise and turns right, the robot travels forward in the forward direction along the passage.
As shown in FIG. 21B, the right-turned passage is a dead end, so the leg-wheel type robot 100 eventually reaches the dead end of the passage.
Since the leg-wheel type robot 100 cannot proceed any further (ascertained by various sensors), the leg-wheel type robot 100 turns 180 [°] and turns back the passage.

Here, since the width of the passage is not wide enough to make a turning motion (for example, U-turn) with back-and-forth movement, as in the case of the right turn, the mode shifts to the super turning control mode, It turns 180 [°], changes the direction of the leg wheel type robot 100, and turns it back.
Further, as shown in FIG. 21 (b), since the passage width is the minimum width of rotation, it is necessary to turn the leg wheel type robot 100 with the minimum turning radius. Therefore, the turning center coordinates (0, 0), the turning angular velocity Ω (the angular velocity for rotating the base 10 clockwise), and the turning angle 180 [°] are input. Note that the posture of each leg 12 of the leg wheel type robot 100 is changed to the knee extension posture so that the leg 12 does not hit the passage.

When the turning center coordinates (0, 0), turning angular velocity Ω, and turning angle 180 [°] are input, the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ _{30 are set} as “θ _{00 = θ 10 = θ 20 =} θ 30 = - (π / 2-φ) "is calculated as the linear velocity _{V 0, V 1, V 2} , V 3, " V ₁ = V ₂ = LΩ "," V ₀ = V ₃ = −LΩ ”is calculated.
Further, the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are converted into rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ according to the above equation (3).

When the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ and the rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω _{3 of the} drive wheels 20 are calculated, the command values are calculated, and the joint motor 40 and The wheel motor 50 is driven.
As a result, the leg wheel type robot 100 turns 180 [°] clockwise (super turning) on the spot without moving back and forth, with the center coordinate (0, 0) of the base body 10 as the turning center, and in the back direction. Change direction.

  Here, for example, when the leg-wheel type robot 100 is travel-controlled manually by remote operation, or when it is automatically controlled and has various sensors and cameras on the back side of the base body 10, no change is made. By running control, it is also possible to run straight back while turning forward and turn the path back. However, in the case of automatic control and when various sensors are provided only on the front side of the base body 10, it is necessary to match the direction of the base body 10 with the traveling direction. Accordingly, in the latter case, the super-symbol turning is a useful turning means.

Next, the operation of the leg-wheel type robot 100 at the time of turning center offset type super-revolution turning control will be described.
Now, it is assumed that the mode is shifted to the wheel traveling mode, each joint motor 40 of the leg wheel type robot 100 is controlled, and the posture of the robot is changed to the knee flexion posture. At this time, it is assumed that the center of gravity of the robot becomes a position deviated from the coordinates of the center position of the base 10 as shown in FIG.

In this case, since the position of the center of gravity is deviated from the coordinates (0, 0) of the center position of the base body 10, if super turning is performed with the center position as the turning center, the turning becomes unbalanced and a problem may occur. There is.
In such a case, in the super-revolution turn control command mode of the present embodiment, since the super-revolution can be made at an arbitrary turning center, the turning angular velocity Ω is input and the leg wheel in the base body 10 is input. The coordinates (xg, yg) corresponding to the center of gravity position of the robot 100 are input as the turning center coordinates (xc, yc).

When the turning angular velocity Ω and the turning center coordinates (xc, yc) = (xg, yg) are input, the x axis of the base 10 and the rotation center of each drive wheel 20 are formed based on the above equation (7). The angles φ ₀ , φ ₁ , φ ₂ , φ ₃ are calculated.
Once the angles φ ₀ , φ ₁ , φ ₂ , and φ ₃ with respect to the rotation center of each drive wheel 20 are calculated, next, steering for making the movement direction of each rotation wheel coincide with the traveling direction of each drive wheel 20. The angles θ ₀₀ , θ ₁₀ , θ ₂₀ , and θ ₃₀ are calculated.

The steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , and θ ₃₀ are calculated as “θ _i0 = − (π / 2−φ _i ) (i = 0, 1, 2, 3)”.
Next, distances L ₀ , L ₁ , L ₂ , and L ₃ between the rotation center around the yaw axis and the turning center (xc, yc) at the time of steering of each drive wheel 20 are calculated based on the above equation (8). .
Once the distances L ₀ , L ₁ , L ₂ , L ₃ are calculated, the linear velocities V ₀ , V ₀ of the drive wheels 20 are then calculated from these distances and the turning angular velocity Ω based on the above equation (9). ₁ , V ₂ and V ₃ are calculated.

Here, assuming that the leg-wheel type robot 100 is turned counterclockwise (Ω> 0), the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are “V ₀ = −L ₀ Ω”, “V ₁ = L ₁ Ω ”,“ V ₂ = L ₂ Ω ”, and“ V ₃ = −L ₃ Ω ”.
Further, the linear velocities V ₀ , V ₁ , V ₂ , V ₃ are converted into rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω ₃ according to the above equation (3).

Once the steering angles θ ₀₀ , θ ₁₀ , θ ₂₀ , θ ₃₀ and the rotational angular velocities ω ₀ , ω ₁ , ω ₂ , ω _{3 of the} drive wheels 20 are calculated, then, via the angle capture I / F 62. Thus, the current steering angle and rotational angular velocity of each drive wheel 20 are acquired. Here, a difference value between the acquired steering angle and the calculated steering angle is calculated, and a command value for driving the joint motor 40 of the rotary joint 14 is calculated based on the difference value. Further, a difference value between the acquired current rotation angular velocity and the calculated rotation angular velocity is calculated, and a command value for driving the wheel motor 50 of the drive wheel 20 is calculated based on the difference value.

  The CPU 60 inputs the calculated steering control command value and speed control command value of each drive wheel 20 to the driver of each motor. By this command value, each joint motor 40 and each wheel motor 50 are driven, whereby the leg wheel type robot 100 is balanced with the coordinates (xg, yg) corresponding to the center of gravity coordinates in the base body 10 as the turning center. Turn the superstrate counterclockwise in the state.

Thus, in the present embodiment, the in-plane scanning leg tip sensor 38 that is rotatably provided on the leg 12 so that the angle formed by the measurement direction with respect to the extending direction of the leg 12 changes, And a motor 82 for rotating the in-plane scanning leg tip sensor 38, and recognizes an obstacle based on the measurement results measured at different rotation angles by the in-plane scanning leg tip sensor 38.
Thereby, since the two-dimensional shape of the obstacle can be recognized, the obstacle avoidance operation can be performed more reliably.

Further, in the present embodiment, the joint motor 40 and the wheel motor 50 are controlled so that the leg-wheel type robot 100 travels in the target traveling direction while maintaining the orientation of the base body 10 in a certain direction.
Thereby, since it is possible to move in any direction without turning (without changing the direction), it is possible to realize quick movement in each direction, and it is impossible to make a turn because each component of the leg-wheel type robot 100 is hindered. Even in areas where it is difficult to change the direction of the leg-wheel type robot, such as a narrow and intricate area, activities can be performed.

  Further, in the present embodiment, the joint motor 40 and the wheel motor 50 are controlled so that the leg wheel type robot 100 turns without moving back and forth at a predetermined turning center position (super turning). At this time, control using the coordinates of the center position on the base body 10 as the turning center coordinates (super-spinning turning control) and control using coordinates other than the center position on the base body 10 as the turning center coordinates (turning center offset type super-spinning turning) Control).

  Thereby, when the center position of the base body 10 is set as the turning center position, the leg-wheel type robot can be turned with the minimum turning radius. Further, when the center position other than the center position of the base body 10 is set as the turning center position, when the center position of the base body 10 and the center of gravity position are different, the center wheel position can be used as a turning center, so that the super wheel can be turned. It is possible to turn the robot 100 in a balanced manner.

  In the second embodiment, the in-plane scanning leg tip sensor 38 corresponds to the distance measuring sensor of the invention 1 to 5 or 7, the motor 82 corresponds to the actuator of the invention 1, 3 or 4, and step S108. S118 corresponds to the obstacle recognition means of the invention 1 or 5, and the joint motor 40 corresponds to the second actuator of the invention 5, 9 or 10. Steps S126 and S128 correspond to the control means of the fifth aspect of the invention, and the non-turning traveling performance control process, the super turning process, and the turning center offset type super turning process by the CPU 60 are the same as those of the ninth or tenth aspect. Corresponds to the control means.

In the first and second embodiments, the in-plane scanning leg tip sensor 38 is provided so as to be rotatable in the same direction as the rotation axis of the rotary joint 18. However, the present invention is not limited to this, as shown in FIG. Further, it may be provided so as to be rotatable in two directions, the same direction as the rotation axis of the rotary joint 18 and a direction orthogonal thereto. Thereby, the three-dimensional shape of an obstacle can be measured.
FIG. 12 is a diagram showing a case where the in-plane scanning leg tip sensor 38 is provided so as to be rotatable about two axes.

In the above embodiment, the drive control of the leg 12 has not been described in detail. For example, as shown in FIG. By adopting walking that actively uses (14 rotations), a three-dimensional peripheral shape can be measured.
FIG. 13 is a diagram illustrating a case where the leg portion 12 is rotated around the yaw axis during the elevation control.

  In the first and second embodiments, the coordinates of the coordinate system of the in-plane scanning leg tip sensor 38 are converted to the global coordinate system, and control is performed based on the conversion result. Not limited to this, as shown in FIG. 14, the measurement data of the in-plane scanning leg tip sensor 38 can be converted into orthogonal coordinates on the sensor measurement plane, and control can be performed based on the conversion result. .

FIG. 14 is a diagram illustrating a case where measurement data of the in-plane scanning leg tip sensor 38 is converted into orthogonal coordinates on the sensor measurement plane.
In the first and second embodiments, the leg 12 is controlled to move up and down based on the measurement data of the in-plane scanning leg tip sensor 38. However, the present invention is not limited to this. As shown, an obstacle existing on the movement path of the leg wheel type robot 100 is recognized based on the measurement data of the in-plane scanning leg tip sensor 38, and the travel control of the leg wheel type robot 100 is controlled based on the recognition result. It can also be configured to do.

FIG. 15 is a diagram illustrating a case where the traveling control of the leg wheel type robot 100 is performed.
Further, in the first and second embodiments, the in-plane scanning leg tip sensor 38 is provided without being inclined about the yaw axis with respect to the leg portion 12, but the present invention is not limited to this and is shown in FIG. As described above, the leg portion 12 may be provided with an inclination of a predetermined angle α around the yaw axis. Thereby, the obstacle ahead can be recognized prior to the movement of the leg portion 12.

FIG. 16 is a diagram showing a case where the in-plane scanning leg tip sensor 38 is provided to be inclined at a predetermined angle α around the yaw axis with respect to the leg portion 12.
In the first and second embodiments, the driving control of the joint motor 40 is started after completion of the measurement by the in-plane scanning leg tip sensor 38. However, the present invention is not limited to this. The driving control of the joint motor 40 may be started during the measurement by the scanning leg tip sensor 38.

Further, in the first and second embodiments, the in-plane scanning leg tip sensor 38 is provided on the outer surface facing the outside of the base 10 of the leg 12, but is not limited thereto, and the base of the leg 12 is not limited thereto. 10 may be provided on the inner side facing the inner side of 10, or may be provided on both the inner side and the outer side.
In the first and second embodiments, the leg-wheel robot according to the present invention is applied to the case where the robot goes over the stairs. However, the present invention is not limited to this. Can be applied.

In the first and second embodiments, the in-plane scanning leg tip sensor 38 is positioned and measured each time by the motor 82. However, the present invention is not limited to this, and the in-plane scanning leg tip sensor 38 is not limited thereto. Can be rotated at a constant speed, the distance can be measured at regular intervals (every constant angle), and a data set of scanning angle and measurement distance can be obtained.
In the first and second embodiments, as shown in FIG. 17A, the distance measuring sensor itself is rotated. However, the present invention is not limited to this, and any optical distance measuring sensor may be used. As shown in FIG. 17B, a mirror inserted on the optical axis in the measurement direction may be rotated.

FIG. 17 is a diagram illustrating a configuration when the measurement direction of the distance measuring sensor is changed.
In the first and second embodiments, the configuration of the leg-wheel type robot 100 according to the present invention is such that the base 10 has a pair of four legs 12 on the front side and a pair of left and right sides on the rear side. However, the present invention is not limited to this, such as a configuration in which a pair of left and right legs 12 is provided in the center of the base 10, a configuration in which three legs 12 are provided symmetrically, a configuration in which five or more legs 12 are provided, and the like. Other configurations may be used without departing from the spirit of the invention. In the case of a multi-legged configuration, the unnecessary leg 12 may be controlled so as not to be used for traveling control.

[Third Embodiment]
Next, a third embodiment of the present invention will be described with reference to the drawings. 23 to 41 are diagrams showing a third embodiment of the leg-wheel type robot, the object recognition apparatus, and the object recognition method according to the present invention.

First, the configuration of a leg wheel type robot 100 to which the present invention is applied will be described.
FIG. 23 is a front view of the leg wheel type robot 100.
FIG. 24 is a side view of the leg wheel type robot 100.
As shown in FIG. 23 and FIG. 24, the leg-wheel type robot 100 includes a base body 10 and four leg portions 12 connected to the base body 10.

Two legs 12 are connected to the front portion of the base body 10 via a rotary joint 14 at symmetrical positions. In addition, two legs 12 are connected to the rear part of the base body 10 via a rotary joint 14 at symmetrical positions. The rotary joint 14 rotates with the direction orthogonal to the bottom surface of the leg wheel type robot 100 as an axial direction. That is, it rotates around the yaw axis.
Each leg portion 12 is provided with two rotary joints 16 and 18. The rotary joint 14 rotates with the lower side as the axial direction, and the rotary joints 16 and 18 rotate with the direction orthogonal to the side surface of the leg wheel type robot 100 as the axial direction when the rotary joint 14 is in the state of FIG. . That is, when the rotary joint 14 is in the state of FIG. 23, it rotates around the pitch axis, and when the rotary joint 14 is rotated 90 degrees from the state of FIG. 23, it rotates around the roll axis. Therefore, each leg 12 has three degrees of freedom.

A driving wheel 20 is rotatably provided at the tip of each leg 12 with the same axial direction as the rotary joints 16 and 18.
At the tip of each leg 12, a front leg tip sensor 22 for measuring the distance to an object existing on the movement path of the leg wheel type robot 100 and a lower leg tip sensor 24 for measuring the distance to the ground plane are provided. Is provided.

  On the other hand, a three-dimensional distance measuring device 200 is attached to the front surface of the base body 10. The coordinate system (hereinafter referred to as a sensor coordinate system) of the three-dimensional distance measuring apparatus 200 has a depth (front-rear length) direction of the base body 10 as an xrs axis, and a width (left-right length) direction of the base body 10 as a yrs axis. The height direction of the substrate 10 is the zrs axis, the xrs axis is the front of the substrate 10, the yrs axis is the right side of the substrate 10, and the zrs axis is the positive direction above the substrate 10.

Next, the external structure of the three-dimensional distance measuring device 200 will be described.
FIG. 25 is a front view (yrs-zrs plane) of the three-dimensional distance measuring apparatus 200.
FIG. 26 is a side view (xrs-zrs plane) of the three-dimensional distance measuring apparatus 200.
FIG. 27 is a top view (yrs-xrs plane) of the three-dimensional distance measuring apparatus 200.
25 to 27, the three-dimensional distance measuring apparatus 200 is provided above the lower support plate 204, the upper support plate 206 provided above the lower support plate 204, and the upper support plate 206. The camera support plate 208 is configured. The lower support plate 204 and the upper support plate 206, and the upper support plate 206 and the camera support plate 208 are supported by a plurality of columns, respectively.

As shown in FIG. 26, the camera support plate 208 is provided so as to protrude in the positive direction of the xrs axis with respect to the lower support plate 204 and the upper support plate 206. A camera 222 is attached to the protruding portion of the camera support plate 208.
A motor 216 is attached to the lower surface of the lower support plate 204. A rotation shaft of the motor 216 (hereinafter referred to as a drive rotation shaft) penetrates the lower support plate 204 from below and is connected to a pulley 220 a disposed between the lower support plate 204 and the upper support plate 206. .

  On the other hand, a two-dimensional distance measuring device 212 is attached to a lower surface of the lower support plate 204 at a position spaced apart from the motor 216 in the horizontal direction by a predetermined distance. The two-dimensional distance measuring device 212 has a rotation shaft (hereinafter referred to as a driven rotation shaft), and the driven rotation shaft passes through the lower support plate 204 from below, and is between the lower support plate 204 and the upper support plate 206. The pulley 220b is connected to the pulley 220b.

A belt 221 is wound around the pulleys 220a and 220b. Accordingly, when the pulley 220a is rotated by the motor 216 and the pulley 220b is rotated by the belt 221 wound around the pulley 220a, the two-dimensional distance measuring device 212 rotates around the zrs axis as shown in FIG.
FIG. 28 is a diagram illustrating a scanning range of the distance measuring sensor.

  The two-dimensional distance measuring device 212 has a built-in distance measuring sensor. As shown in FIG. 28, the two-dimensional distance measuring device 212 rotates at a predetermined scanning unit angle while rotating the distance measuring sensor about the zrs axis and an axis orthogonal to the measurement direction. The measurement result of the distance measuring sensor is acquired. The scanning range of the distance measuring sensor is set so that the leg wheel type robot 100 scans mainly below the leg wheel type robot 100 because the leg wheel type robot 100 is intended to move up and down stairs and avoid obstacles. . At the origin position of the two-dimensional distance measuring device 212 and the distance measuring sensor (the positions where the scanning angles θ and φ are 0 °), the measuring direction of the distance measuring sensor coincides with the xrs axis, and the rotation axis of the distance measuring sensor is It matches the yrs axis. Although the direction of the rotation axis of the distance measurement sensor changes depending on the scanning angle of the two-dimensional distance measurement device 212, it coincides with the yrs axis at the origin position. Therefore, for convenience of explanation, the rotation axis of the distance measurement sensor is expressed as the yrs' axis. To do.

  In the three-dimensional distance measuring apparatus 200, the rotation driving mechanism (motor 216, encoder 218, pulleys 220a and 220b, belt 221 and lower support plate 204) that rotates and drives the two-dimensional distance measuring apparatus 212 has a scanning range shown in FIG. Since it is provided outside, within the scanning range shown in FIG. 28, the scanning of the distance measuring sensor 212a is not hindered by each mechanism part constituting the three-dimensional distance measuring device 200.

  Further, since it is only necessary to be able to recognize an obstacle on the travel route of the leg-wheel type robot 100, the scanning range by the rotational drive around the zrs axis does not need to cover up to 180 ° forward, and the horizontal range from the two-dimensional distance measuring device 212 is not necessary. A range in which the motor 216 and the encoder 218 arranged at a predetermined distance in the direction are out of the scanning range is also sufficient. Therefore, the rotational driving range of the two-dimensional distance measuring device 212 is set to a range not including the motor 216 and the encoder 218.

Next, the movement control system of the leg wheel type robot 100 will be described.
FIG. 29 is a block diagram showing a movement control system of the leg wheel type robot 100.
As shown in FIG. 29, joint motors 40 that rotationally drive the rotary joints 14 to 18 are respectively provided in the rotary joints 14 to 18 of the leg portions 12. Each joint motor 40 is provided with an encoder 42 that detects the rotational angle position of the joint motor 40, and a driver 44 that controls the driving of the joint motor 40 based on the motor command signal and the output signal of the encoder 42.

A wheel motor 50 that rotationally drives the drive wheel 20 is provided on the drive wheel 20 of each leg 12. Each wheel motor 50 is provided with an encoder 52 that detects the rotational angle position of the wheel motor 50, and a driver 54 that controls the driving of the wheel motor 50 based on the motor command signal and the output signal of the encoder 52.
The leg-wheel type robot 100 further includes a CPU 60, a three-axis attitude sensor 70 that detects the attitude of the leg-wheel type robot 100, a wireless communication unit 74 that performs wireless communication with an external PC, the wireless communication unit 74, and the CPU 60. Are provided with a hub 76 that relays the input / output of the sound and a speaker 78 that outputs a warning sound or the like.

The triaxial attitude sensor 70 includes a gyroscope or an acceleration sensor, or both, and detects the inclination of the attitude of the leg wheel type robot 100 with respect to the ground axis.
The CPU 60 outputs motor command signals to the drivers 44 and 54 via the motor command output I / F 61 and inputs output signals of the encoders 42 and 52 via the angle fetch I / F 62. In addition, sensor signals are input from the three-dimensional distance measuring device 200, the front leg tip sensor 22, the lower leg tip sensor 24, and the three-axis posture sensor 70 via the sensor input I / F 63, respectively. Further, signals are input / output to / from the hub 76 via the communication I / F 64, and an audio signal is output to the speaker 78 via the sound output I / F 65.

Next, the control structure of the two-dimensional distance measuring device 212 will be described.
FIG. 30 is a block diagram showing a control structure of the two-dimensional distance measuring device 212.
As shown in FIG. 30, the two-dimensional distance measuring device 212 includes a distance measuring sensor 212a that measures a distance to a measurement point on an object that exists within the measurement range, a motor 212c that rotates the distance measuring sensor 212a, The encoder 212d is configured to detect the rotational angle position of the motor 212c, and the driver 212b is configured to control the driving of the motor 212c based on the command signal and the output signal of the encoder 212d.

The driver 212b has a scanning angle range (for example, a predetermined angle range such as −40 ° to + 40 °) and a scanning unit angle (for example, a predetermined unit such as 0.36 °) set in the command signal from the sensing processor 210. Based on the angle, control is performed to rotate the rotation axis of the motor 212c by a scanning unit angle.
The motor 212c is provided so as to rotate and drive a laser output unit (not shown) and a light receiving unit (not shown) of the distance measuring sensor 212a around the yrs' axis. Are rotated by a scanning unit angle (Δθ).

Next, the control structure of the three-dimensional distance measuring apparatus 200 will be described.
FIG. 31 is a block diagram showing a control structure of the three-dimensional distance measuring apparatus 200.
As shown in FIG. 31, the three-dimensional distance measuring device 200 includes a sensing processor 210, a two-dimensional distance measuring device 212, a motor 216, an encoder 218, a command signal, and an output signal of the encoder 218. A driver 214 that controls driving and a camera 222 are included.

  The sensing processor 210 executes a dedicated program, gives a command signal to the driver 212b, rotates the distance measuring sensor 212a, and is within an area that can be measured within the scanning range of the distance measuring sensor 212a (hereinafter referred to as a scanning plane). A two-dimensional distance measuring device that executes a first scanning process for measuring a distance to a measurement point on an existing object and gives a command signal to the driver 214 each time the first scanning process for one scanning plane is completed. A second scanning process for rotating 212 is executed.

The sensing processor 210 further operates on the object existing in the measurement range based on the distance information (hereinafter referred to as distance information) measured by the two-dimensional distance measurement device 212 through the first scanning process and the second scanning process. The process of recognizing the continuous surface is executed.
Next, the principle of distance measurement of the three-dimensional distance measuring apparatus 200 will be described.
FIG. 32 is a diagram for explaining the principle of distance measurement of the two-dimensional distance measuring device 212.

  As shown in FIG. 32, the two-dimensional distance measuring device 212 is rotated each time the distance measuring sensor 212a rotates by the scanning unit angle around the yrs' axis in accordance with the rotational drive of the rotating shaft of the motor 212c. In addition, laser light is output from the laser output unit, and reflected light from an object (obstacle in FIG. 32) with respect to the output light is received by the light receiving unit, and a distance corresponding to each scanning angle (measurement distance in FIG. 32). L (distance between the object and the light receiving unit)) is measured.

FIG. 33 is a diagram illustrating a case where scanning is performed by the first scanning process and the second scanning process. FIG. 6A is a diagram showing the relationship between the measurement distance L and the scanning angle θ when the distance measurement sensor 212a is rotated about the yrs ′ axis, and FIG. 6B is a two-dimensional distance measurement device. It is a figure which shows the relationship between the scanning plane when 212 is rotated around the zrs axis, and the scanning angle φ.
In the first scanning process, for example, as shown in FIG. 33A, the distance measurement sensor 212a is rotated by the scanning unit angle around the yrs' axis while each scanning angle with respect to the origin position (in FIG. 33A). This is a process for measuring distance information (L (θ ₁ ), L (θ ₂ ), L (θ ₃ ) in FIG. 33A) according to θ ₁ , θ ₂ , θ ₃ ).

In the first scanning process, a plane formed by connecting the rotation center of the rotating shaft of the motor 212c and both ends of the scanning trajectory line of the laser is a scanning plane (a fan-shaped plane when no object is present). .
The driver 214 performs control to rotate the rotation axis of the motor 216 by the scanning unit angle based on the scanning angle range and the scanning unit angle (Δφ) set in the command signal from the sensing processor 210.

  The motor 216 is provided to rotationally drive the two-dimensional distance measuring device 212 around the zrs axis via a speed reducer (not shown), pulleys 220a and 220b, and a belt 221, and receives a control signal from the driver 214. Correspondingly, the rotation axis of the self is rotated by the scanning unit angle. As a result, the rotational driving force is transmitted to the driven rotational shaft via the pulleys 220a and 220b in accordance with the rotational driving of the rotational shaft of the motor 216, and the two-dimensional distance measuring device 212 rotates about the zrs axis by a scanning unit angle. .

That is, the second scanning process is a process of rotating the two-dimensional distance measuring device 212 by the scanning unit angle around the zrs axis as shown in FIG. Then, by performing the first scanning process and the second scanning process alternately and continuously, the scanning plane formed by the first scanning process is continuously formed around the zrs axis.
FIG. 34 is a diagram illustrating a distance measurement example of the three-dimensional distance measuring apparatus 200.

Thereby, for example, as shown in FIG. 34, the three-dimensional shape of an object such as a wall, a wall, a stand, or a shelf can be grasped.
Further, as shown in FIG. 33 (b), the distance information of each measurement point after the second scanning process is expressed as L (θ _i , φ _j ). Here, i is a serial number given to each measurement point according to the scanning angle around the yrs' axis, and j is a serial number given to each measurement point according to the scanning angle around the zrs axis.

Next, an object recognition process executed by the three-dimensional distance measuring apparatus 200 will be described.
FIG. 35 is a flowchart showing object recognition processing executed by the three-dimensional distance measuring apparatus 200.
The object recognition process is a process realized by the sensing processor 210 reading a dedicated program stored in a ROM (not shown) based on a command signal from the CPU 60 and executing the read program. When the process is executed, as shown in FIG. 35, first, the process proceeds to step S200.

In step S200, the three-dimensional distance measuring apparatus 200 sets the scanning angle range and the scanning unit angle of the distance measuring sensor 212a and the two-dimensional distance measuring apparatus 212 based on the command signal from the CPU 60, and the process proceeds to step S202. Here, the command signal from the CPU 60 includes information on the scanning angle range and the scanning unit angle.
In step S202, by outputting a command signal to the two-dimensional distance measuring device 212, the driver 212b, the motor 212c, and the encoder 212d are driven, and the distance measuring sensor 212a is scanned with the scanning angle around the yrs' axis set in step S200. Within the range, the scanning unit angle set in step S200 is rotated around the yrs' axis, and the first scanning process for measuring the distance information corresponding to each scanning angle is executed, and the process proceeds to step S204.

In step S204, a filtering process using a median filter is performed on the distance information measured in step S202 to remove noise components, and the process proceeds to step S206.
In step S206, the distance information of the rotating coordinate system after the noise removal in step S204 is converted into the coordinate information of the orthogonal coordinate system. Thereby, the distance information of each measurement point obtained by the first scanning process is converted into coordinate information of an orthogonal coordinate system (hereinafter referred to as a scanning plane coordinate system) in which the scanning plane of the first scanning process is a two-dimensional plane. Converted.

Next, the process proceeds to step S210, and a line segment in the orthogonal coordinate system is detected by Hough transform based on the coordinate information transformed in step S206.
FIG. 36 is a diagram for explaining the principle of the Hough transform. FIG. 4A shows the xy plane, and FIG. 4B shows the ρ-θ plane. Note that the x-axis and y-axis in FIG. 5A indicate axes in the scanning plane coordinate system and are separate from the axes in the sensor coordinate system.

  The Hough transform is one of feature extraction methods used in digital image processing. Classically, it used to detect straight lines, but it is more generalized and used for various forms (those that can be expressed in the form of equations such as circles and ellipses). A feature of the Hough transform is that a relatively good result can be obtained even when a straight line in the image is cut off in the middle or when noise exists.

Consider a straight line ax + by + c = 0 in the scanning plane coordinate system as shown in FIG.
When a perpendicular is drawn from this straight line to the origin, the length of the perpendicular is ρ, and the angle between the perpendicular and the x axis is θ, this straight line can be expressed by the following equation (10).

The above equation (10) can be transformed into the following equation (11).

ρ = xcosθ + ysinθ (11)

Therefore, one straight line corresponds to one set of (ρ, θ). Here, the point (ρ, θ) is referred to as the Hough transform of the straight line ax + by + c = 0. A straight line group passing through an arbitrary point (x0, y0) in the scanning plane coordinate system can be expressed by the following equation (12).

ρ = x0cosθ + y0sinθ (12)

Here, when a locus of each straight line group passing through the three points P1, P2, and P3 on the xy plane is drawn on the ρ-θ plane, a sinusoidal curve is obtained as shown in FIG. If these three points exist on the same line in the xy plane, the values of ρ and θ are the same, and the curves corresponding to the three points intersect at one point on the ρ-θ plane.

If the principle of the Hough transform is used, a line segment can be detected based on the coordinates of a plurality of measurement points. That is, for n (n ≧ 2) measurement points, n curves are drawn on the ρ-θ plane, and m (n ≧ m ≧ 2) curves among them intersect at one point. For example, the m measurement points corresponding to the m curves are on the same straight line in the xy plane.
Next, as shown in FIG. 35, the process proceeds to step S <b> 220, and the end point of the detected line segment is determined as the boundary (continuous edge) of the continuous surface. When multiple line segments overlap or when multiple line segments exist within a predetermined distance, it is considered as one line segment, and the two farthest points among the end points of these line segments are Judge as a boundary.

Next, the process proceeds to step S224, where the coordinate information of the endpoint determined as the boundary of the continuous surface is converted into a sensor coordinate system, and the converted coordinate information is associated with each line segment in a memory (not shown) such as a RAM. Store, and the process proceeds to step S226.
In step S226, it is determined whether or not the processing of steps S202 to S224 has been completed for all scanning planes corresponding to the scanning angle range and scanning unit angle of the second scanning processing, and when it is determined that the processing has ended (Yes) ) Proceeds to step S236.

  In step S236, surface data is generated based on the coordinate information stored in the memory. Since the line segment connecting the end points determined as the boundary of the continuous surface (which is regarded as one line segment in step S220) is an intersection line where the continuous surface and the scanning plane intersect, generation of surface data is, for example, The slope and coordinates of the line segment connecting the end points determined as the boundary of the continuous surface in a certain scanning plane and the line segment connecting the end points determined as the boundary of the continuous surface in the scanning plane adjacent to the zrs axis are within a predetermined range. Are determined as continuous surfaces, coordinate information corresponding to these line segments is associated, or connected by using a known interpolation method. For example, since a continuous surface having an inclination close to 0 can be regarded as a horizontal surface, it can be determined that the surface is a walking surface.

Next, the process proceeds to step S238, where the surface data generated in step S236 is output to the CPU 60 via the hub 76 and the communication I / F 64, and the series of processes is terminated.
On the other hand, when it is determined in step S226 that the processes in steps S202 to S224 are not completed for all scanning planes (No), the process proceeds to step S240, and a command signal is output to the three-dimensional distance measuring device 200. The driver 214, the motor 216, and the encoder 218 are driven, and the two-dimensional distance measuring device 212 is rotated around the zrs axis by the scanning unit angle set in step S200 within the scanning angle range around the zrs axis set in step S200. The second scanning process is performed, and the process proceeds to step S202.

Next, processing executed by the CPU 60 will be described.
The CPU 60 activates a control program stored in a predetermined area such as a ROM, and executes the elevation control process shown in the flowchart of FIG. 37 according to the control program.
FIG. 37 is a flowchart showing the elevation control process.
The elevation control process is a process for performing the elevation control of the leg portion 12. When the elevation control process is executed by the CPU 60, the process first proceeds to step S300 as shown in FIG.

In step S300, surface data is input from the three-dimensional distance measuring device 200, the process proceeds to step S302, and the coordinates of each measurement point in the sensor coordinate system are converted to the coordinates of the global coordinate system based on the input surface data. A point on the periphery of the continuous surface is detected as a feature point of the staircase.
Next, the process proceeds to step S304, the width of the staircase is calculated based on the detected feature point of the staircase, and the process proceeds to step S306, where the actual coordinates of the stair nosing part of the staircase are calculated based on the detected feature point of the staircase. Then, the process proceeds to step S308.

In step S308, inverse kinematics calculation and centroid calculation are performed based on the calculated width of the staircase and the actual coordinates of the stair nose and the sensor signal of the three-axis posture sensor 70. The process proceeds to step S310, and the calculation result of step S308 is obtained. The landing position of the leg tip (drive wheel 20) is determined based on the above, and the process proceeds to step S312.
In step S312, sensor signals are input from the front leg tip sensor 22 and the lower leg tip sensor 24, respectively, and the process proceeds to step S314 to calculate the distance to the kick plate based on the input sensor signal of the front leg tip sensor 22. Then, the process proceeds to step S316, the positional relationship between the leg tip and the tread is calculated based on the input sensor signal of the lower leg tip sensor 24, and the process proceeds to step S318.

In step S318, a motor command signal to the drivers 44 and 54 is generated based on the determined landing position and the calculated both distances, the process proceeds to step S320, and the generated motor command signal is output to the drivers 44 and 54. Control goes to step S322.
In step S322, it is determined whether or not the leg tip has landed on the tread. When it is determined that the leg tip has landed (Yes), the series of processes is terminated and the process returns to the original process.

On the other hand, when it is determined in step S322 that the leg tip does not land (No), the process proceeds to step S312.
Next, the operation of the present embodiment will be described.
A case will be described in which a stairway exists on the movement path of the leg-wheel type robot 100 and the stairs are overcome.

In the sensing processor 210, first, the scanning angle range and the scanning unit angle are set in the sensing processor 210 based on a command signal from the CPU 60 through step S200.
Here, it is assumed that the two-dimensional distance measuring device 212 is a two-dimensional range sensor having a distance measurement range of 20 to 4095 [mm], a maximum scanning angle range of 240 °, and an angular resolution of 0.36 °. If the scanning angle range is 240 °, it is the same as the scanning angle range forming the scanning plane shown in FIG. 28, and the lower support plate 204, the pulleys 220a and 220b, and the belt 221 above the two-dimensional distance measuring device 212 are provided. It will not be included in the scanning range.

  Further, a scanning angle range of 240 ° and a scanning unit angle of 0.36 ° are set for the first scanning process, and a scanning angle range of −40 ° to + 40 ° and a scanning unit angle of 10 ° are set for the second scanning process. Is set (in this case, nine scanning planes are formed). If the scanning angle range is −40 ° to + 40 °, the motor 216 and the encoder 218 arranged at a predetermined distance in the horizontal direction from the two-dimensional distance measuring device 212 are not included in the scanning range.

Next, through step S202, the first scanning process is executed by outputting a command signal to the driver 212b based on the scanning angle range and the scanning unit angle set for the first scanning process. Initially, a first scanning process is performed on a position (origin position) where the scanning angle φ around the zrs axis is 0 °.
As a result, based on the command signal from the sensing processor 210 and the output signal from the encoder 212d, the driver 212b drives the rotation shaft of the motor 212c to rotate, and the distance measuring sensor 212a scan unit angle Δθ = about the yrs ′ axis. While rotating by 0.36 °, the distance corresponding to each scanning angle is measured. Each distance information is output to the sensing processor 210 as a data string L (θ _i , φ _j ).

In the scanning range around the yrs' axis, there is no object other than the base 10 that obstructs scanning, such as the driving mechanism of the two-dimensional distance measuring device 212. Distance information can be obtained.
When the first scanning process for one scanning plane is completed, the filtering process is performed on the distance information measured in the first scanning process through step S204. Thereby, the noise component in measurement information is removed.

FIG. 38 is a graph showing a measurement result by the first scanning process.
Here, the measurement distance L [mm] of each measurement point after removing the noise component is as shown in FIG. 38, for example. In FIG. 38, the horizontal axis is the number of the measurement point corresponding to each scanning angle (first scanning angle number), and the vertical axis is the measurement distance L [mm] to the measurement point of each scanning angle number.
In the example of FIG. 38, it can be seen that there are stairs on the walking path of the leg-wheel type robot 100 with a constant step and a tread board as a continuous surface.

Next, through step S206, the distance information of the rotated coordinate system after the filtering process is converted into the coordinate information of the orthogonal coordinate system.
FIG. 39 is a graph showing the result of converting the distance information of the rotating coordinate system of each measurement point of FIG. 38 into the coordinate information of the orthogonal coordinate system.
The distance information of the rotational coordinate system of each measurement point in FIG. 38 is obtained by coordinate conversion, as shown in FIG. 39, the distance [mm] in the xrs axis direction and the distance [mm] in the zrs axis direction corresponding to each scanning angle. Is two-dimensional coordinate information. In FIG. 39, the horizontal axis represents the distance L _x [mm] in the xrs axis direction, and the vertical axis represents the distance L _z [mm] in the zrs axis direction.

Next, through step S210, a line segment in the orthogonal coordinate system is detected by Hough transform based on the transformed coordinate information.
FIG. 40 is a graph showing the measurement points in the orthogonal coordinate system and the results of the Hough transform.
In the orthogonal coordinate system, each measurement point is represented as a set of a plurality of points along the contours of the kick board and the tread board, as shown in FIG. In the example of FIG. 40 (a), in the region corresponding to the first step tread, some measurement points are distributed in a region deviating from the continuous surface. The measurement results vary due to the influence of the error area A1. The area A2 has a lower measurement resolution than the other areas.

When the Hough transform is performed on the measurement result, as shown in FIG. 40B, a line segment along the outline of each tread is detected.
As another method for detecting a line segment based on a plurality of measurement points, a least square method is known.
However, in the least square method, line segments are detected by tracing each measurement point, and therefore, in the low resolution area A2, a line segment that does not follow the contour of the tread may be detected. On the other hand, in the Hough transform, it is difficult to be affected by the measurement resolution, and even if the low resolution region A2 is included, a line segment relatively along the contour of the tread is detected as shown in FIG. Can do.

  Further, in the least square method, line segments are detected by tracing each measurement point, so that the error region A1 is detected as an oblique line segment that is actually a flat line segment. On the other hand, in the Hough transform, if it is not easily affected by variations and the number of variations is small, the error region A1 and the regions on both sides thereof can be detected as flat line segments as shown in FIG. it can.

  Further, the least square method has a problem as to whether to recognize a region from where to where is one continuous surface. In this case, for example, it is conceivable to recognize a point where the slope of the detected line segment changes abruptly as the boundary of the continuous surface. However, in this recognition method, the error region A1 is actually the error region A1 and the regions on both sides thereof. Is a single continuous surface, the regions on both sides are recognized as separate continuous surfaces. On the other hand, in the Hough transform, if it is not easily affected by the variation and the number of variations is small, the error region A1 and the regions on both sides thereof are detected as one flat line segment as shown in FIG. be able to.

Next, through steps S220 and S224, the end point of the detected line segment is determined as the boundary of the continuous surface, the coordinate information of the end point determined as the boundary of the continuous surface is converted into the sensor coordinate system, and the converted coordinate information Is stored in the memory.
When the measurement is completed for one scanning plane, the second scanning is performed by outputting a command signal to the driver 214 based on the scanning angle range and the scanning unit angle set for the second scanning process through step S240. Processing is executed.

  As a result, based on the command signal from the sensing processor 210 and the output signal from the encoder 218, the driver 214 rotates the rotation axis of the motor 216, and the two-dimensional distance measurement device 212 has a scanning unit angle of 10 around the zrs axis. Rotate by °. By the second scanning process, the orientation of the two-dimensional distance measuring device 212 changes by 10 ° around the zrs axis with respect to the previous state. In this state, the first scanning process is executed again through step S202. That is, a new scanning plane is formed at a position shifted by 10 ° around the zrs axis, and the first scanning process is performed on this scanning plane.

Here, since the two-dimensional distance measuring device 212 is attached to the front surface of the base body 10, the base body 10 is included in the scanning range, but in the range including the front of the leg wheel type robot 100 and the walking path. Since there are no obstructions, it can be said that a sufficient scanning range for performing the walking control of the leg-wheel type robot 100 can be secured.
When the measurement is completed for all the scanning planes, plane data is generated based on the coordinate information stored in the memory through step S236.

FIG. 41 is a diagram illustrating determination results of continuous surfaces.
As shown in FIG. 41, the plane data is generated by connecting line segments having similar inclinations and coordinates between adjacent scanning planes around the zrs axis. In the example of FIG. 41, for example, the line segment of the region (φ0, 2) corresponding to the first step board on the scanning plane φ0 and the region (φ1, 2) corresponding to the first step plate on the scanning plane φ1. ) Is determined to constitute one continuous surface, surface data in which the coordinate information of the end points of the line segments is associated is generated for the continuous surface.

  Similarly, the line segment of the region (φ0, 2i (i is an integer greater than or equal to 2)) in the scan plane φ0 and the line segment of the region (φ1, 2i) in the scan plane φ1 represent one continuous plane, and the scan plane φ0 It is determined that the line segment of the region (φ0, 2j (j is an integer equal to or greater than 1) -1) and the line segment of the region (φ1, 2j-1) on the scanning plane φ1 constitute one continuous surface, and the plane data is Generated.

The surface data is output to the CPU 60 via the hub 76 and the communication I / F 64 through step S238.
When the surface data is input, the CPU 60 detects the feature point of the staircase based on the input surface data through step S302. In addition, the input surface data is analyzed, and for example, a continuous surface whose inclination is close to 0 is regarded as a horizontal surface, and it is determined that the leg-wheel type robot 100 can walk.

If it is determined that the face is a walkable surface, the width of the staircase and the actual coordinates of the stair nose are calculated based on the detected feature points of the staircase through steps S304 to S310. The landing position of the leg tip is determined based on the real coordinates of the part.
Further, through steps S312 to S316, sensor signals are input from the leg tip sensors 22 and 24, respectively, and the distance to the kick plate and the positional relationship between the leg tip and the tread plate are calculated. Then, through steps S318 and S320, a motor command signal is generated based on the determined landing position and both calculated distances, and the generated motor command signal is output to the drivers 44 and 54. As a result, the driving wheel 20 rotates and the rotary joints 14 to 18 are driven, and the leg-wheel type robot 100 gets over the stairs while keeping its posture properly. Depending on the situation, the stairs are avoided and stopped. Therefore, the adaptability to the stairs is high like the legged robot.

In addition, although the step is given as an example, the staircase where the step board is a continuous surface is given as an example, but the step can be accurately recognized even for a staircase where the step is not constant, a staircase without a kick plate, etc. The adaptability to the stairs of the leg wheel type robot 100 can be improved.
On the other hand, on a flat ground, the leg-wheel type robot 100 can move by wheel running. Therefore, the mobility on the flat ground is high like the wheel type robot.

  As described above, in this embodiment, the distance measuring sensor 212a that measures the distance to the measurement point on the object is provided, the distance measurement sensor 212a is scanned, and the distance measurement sensor can be measured for the measurement points that can be measured in the scanning range. The measurement result of 212a is acquired, the acquired measurement result is converted into the coordinates of the orthogonal coordinate system, and the line segment in the orthogonal coordinate system is detected by the Hough transform based on the converted coordinates of the at least two measurement points, and detected. Recognize continuous faces or boundaries of continuous faces based on line segments.

  Accordingly, since at least the planar shape of the object can be grasped as a continuous surface or a boundary between continuous surfaces, the posture control of a robot that requires complicated posture control, such as the legged robot or the legged wheel type robot 100, is possible. A suitable recognition result can be obtained. Further, since the line segment is detected by the Hough transform, when the object recognition is performed by the two-dimensional distance measuring device 212 using the distance measuring sensor 212a, there is a possibility that the recognition accuracy may be lowered due to a decrease in measurement resolution or a variation in measurement results. Can be reduced.

Furthermore, as compared with the least square method, robust detection can be performed for an edge that is difficult to detect.
Furthermore, in this embodiment, the continuous surface or the boundary of the continuous surface is recognized based on the coordinates of the end points of the detected line segment.
Thereby, the continuous surface or the boundary of the continuous surface can be recognized relatively accurately.

  Further, in the present embodiment, a yrs′-axis rotation mechanism including a motor 212c and the like that rotates the ranging sensor 212a around the yrs ′ axis, and a zrs axis including a motor 216 and the like that rotates the ranging sensor 212a around the zrs axis. A first scanning for obtaining a measurement result of the distance measuring sensor 212a for each scanning unit angle of the yrs 'axis rotating mechanism while rotating the distance measuring sensor 212a by the yrs' axis rotating mechanism. By performing the second scanning performed for each scanning unit angle of the zrs axis rotation mechanism while rotating the distance measuring sensor 212a, the measurement is performed for each scanning unit angle of the yrs' axis rotation mechanism and for each scanning unit angle of the zrs axis rotation mechanism. Get the result.

  As a result, the three-dimensional shape of the object can be grasped as a continuous surface or a boundary between the continuous surfaces, so that the posture control of a robot that requires complicated posture control, such as the legged robot or the leg-wheel type robot 100, is possible. A more suitable recognition result can be obtained. In addition, since a rotation mechanism that rotates the distance measuring sensor 212a is adopted, a space required for scanning is smaller than that of the moving mechanism, the scanning mechanism is simplified, and high-speed scanning is realized. Can do.

Furthermore, in this embodiment, the motor 216 and the encoder 218 and the two-dimensional distance measuring device 212 are arranged at a predetermined distance in the horizontal direction, and the rotational driving force of the driving rotary shaft is set to the pulley 220a, the belt 221 and the pulley 220b. The two-dimensional distance measuring device 212 is driven to rotate about the zrs axis.
As a result, there is no obstacle to scanning within the scanning angle range of the two-dimensional distance measuring device 212, so that accurate distance information can be obtained. Further, since the motor 216 and the encoder 218 and the two-dimensional distance measuring device 212 are arranged in the horizontal direction, the occupation ratio in the height direction of the three-dimensional distance measuring device 200 can be reduced.

Further, in the present embodiment, leg tip sensors 22 and 24 are provided, the stairs are recognized based on the distance measured by the leg tip sensors 22 and 24, and the motors 40 and 50 are controlled based on the recognition result.
Thereby, since the raising / lowering control of the leg part 12 is performed while recognizing the unknown staircase using the leg tip sensors 22 and 24, it is possible to realize higher adaptability to the unknown staircase than in the past. . In addition, since it can operate in an environment where people are active, it is suitable for home robots, personal robots, and the like that are used for acting with people.

Further, in the present embodiment, the three-dimensional distance measuring device 200 is provided on the front surface of the base body 10, and the leg tip sensors 22 and 24 are provided on the distal ends of the leg portions 12.
As a result, it is possible to detect an object existing on the movement path of the leg wheel type robot 100 with a wide field of view, and to accurately measure the distance between the drive wheel 20 and the staircase when moving up and down the stairs.

Further, in the present embodiment, the distance to the stair riser plate is calculated based on the measurement result of the front leg tip sensor 22, and the positions of the drive wheels 20 and the step board of the staircase are calculated based on the measurement result of the lower leg tip sensor 24. Calculate the relationship.
Thereby, since the characteristic more effective for the raising / lowering control of the leg part 12 can be detected among the characteristics of the staircase, higher adaptability can be realized for the unknown staircase.

  In the third embodiment, steps S202 and S240 correspond to the measurement result acquisition unit of the invention 11, 14 or 16, or the measurement result acquisition step of the invention 27, and step S206 includes the coordinate conversion unit of the invention 11, Or it corresponds to the coordinate conversion step of the invention 27. Step S210 corresponds to the line segment detection means of the invention 11, 13 or 15 or the line segment detection step of the invention 27, and steps S220 and S236 correspond to the recognition means of the invention 11, 13 or 15, or the invention 27 It corresponds to the recognition step.

  In the third embodiment, the yrs 'axis corresponds to the first scanning axis of the invention 16, the zrs axis corresponds to the second scanning axis of the invention 16, and the yrs' axis rotation mechanism is the invention. 14 or 16 of the first scanning means or the first rotating means of the sixteenth aspect of the invention, and the zrs axis rotating mechanism corresponds to the second scanning means of the fourteenth or sixteenth aspect of the invention or the second rotating means of the sixteenth aspect of the invention. .

[Fourth Embodiment]
Next, a fourth embodiment of the present invention will be described with reference to the drawings. 42 and 43 are diagrams showing a fourth embodiment of the leg-wheel robot, object recognition apparatus, and object recognition method according to the present invention.

This embodiment differs from the third embodiment in that the Hough transform is performed after connecting the measurement points with line segments in the orthogonal coordinate system. Hereinafter, only the parts different from the third embodiment will be described, and the same parts as those in the third embodiment will be denoted by the same reference numerals and the description thereof will be omitted.
First, an object recognition process executed by the three-dimensional distance measuring apparatus 200 will be described.

FIG. 42 is a flowchart showing object recognition processing executed by the three-dimensional distance measuring apparatus 200.
When the object recognition process is executed in the sensing processor 210, the process proceeds to step S208 through steps S200 to S206 as shown in FIG.
In step S208, the measurement points adjacent in the x-axis direction in the scanning plane coordinate system are connected by line segments based on the coordinate information converted in step S206, and the process proceeds to step S210. A line segment in the orthogonal coordinate system is detected by Hough transform based on the coordinate information of the point.

Then, after steps S220 and S224, the process proceeds to step S226 to determine whether or not the processing of steps S202 to S224 has been completed for all the scanning planes, and when it is determined that the processing has been completed (Yes) Through steps S236 and S238, the series of processes is terminated.
On the other hand, when it is determined in step S226 that the processes in steps S202 to S224 are not completed for all scanning planes (No), the process proceeds to step S202 via step S240.

Next, the operation of the present embodiment will be described.
A case will be described in which a stairway exists on the movement path of the leg-wheel type robot 100 and the stairs are overcome. Since the third embodiment is different from the third embodiment in that a line segment is detected by Hough transform, only different portions will be described.
Through steps S208 and S210, measurement points are connected by line segments based on the converted coordinate information, and line segments in the orthogonal coordinate system are detected by Hough transform based on the coordinate information of the points on the obtained line. .

FIG. 43 is a graph illustrating measurement points, line segment connection results, and Hough transform results in an orthogonal coordinate system.
In the orthogonal coordinate system, each measurement point is represented as a set of a plurality of points along the contours of the kick board and the tread board as shown in FIG. In the example of FIG. 43 (a), in the region corresponding to the first step tread, some measurement points are distributed in a region deviating from the continuous surface. The measurement results vary due to the influence of the error area A1. The area A2 has a lower measurement resolution than the other areas.

When a line segment connection is made for this measurement result, each measurement point is connected by one line as shown in FIG. As a result, between the measurement points where no measurement point exists, the points on the line are interpolated.
When the Hough transform is performed on the connection result, as shown in FIG. 43 (c), a line segment along the outline of each kick board and each tread board is detected.

If the Hough transform is performed on the measurement result in FIG. 43A without connecting the line segments, as shown in FIG. 40B, the line segments along the contours of the treads are detected. The line segment along each kick plate cannot be detected.
As described above, in this embodiment, the distance measuring sensor 212a that measures the distance to the measurement point on the object is provided, the distance measurement sensor 212a is scanned, and the distance measurement sensor can be measured for the measurement points that can be measured in the scanning range. The measurement result of 212a is acquired, the acquired measurement result is converted into coordinates in an orthogonal coordinate system, the converted measurement points are connected by line segments, and orthogonality is obtained by Hough transform based on the coordinates of the points on the obtained line A line segment in the coordinate system is detected, and a continuous surface or a boundary of the continuous surface is recognized based on the detected line segment.

  Accordingly, since at least a planar shape of the object can be grasped as a continuous surface on the object or a boundary between the continuous surfaces, a robot that requires complicated posture control, such as the legged robot or the leg wheel type robot 100. A recognition result suitable for posture control can be obtained. Further, since the line segment is detected by the Hough transform, when the object recognition is performed by the two-dimensional distance measuring device 212 using the distance measuring sensor 212a, there is a possibility that the recognition accuracy may be lowered due to a decrease in measurement resolution or a variation in measurement results. Can be reduced. In addition, since line segments are detected based on the coordinates of points on the line obtained by connecting the measurement points with line segments, relatively accurate recognition results can be obtained even if measurement resolution decreases or measurement results vary. The possibility that the recognition accuracy is lowered can be further reduced.

Furthermore, as compared with the least square method, robust detection can be performed for an edge that is difficult to detect.
In the fourth embodiment, steps S202 and S232 correspond to the measurement result acquisition means of invention 12 or the measurement result acquisition step of invention 28, and step S206 corresponds to the coordinate conversion means of invention 12 or of the invention 28. Corresponding to the coordinate conversion step, step S210 corresponds to the line segment detection means of the invention 12 or the line segment detection step of the invention 28. Steps S220 and S228 correspond to the recognition means of the invention 12 or the recognition step of the invention 28.

[Fifth Embodiment]
Next, a fifth embodiment of the present invention will be described with reference to the drawings. 44 to 51 are diagrams showing a fifth embodiment of the leg-wheel type robot, the object recognition apparatus, and the object recognition method according to the present invention.

  The present embodiment is different from the third embodiment in that the boundary of the continuous surface is recognized based on the measurement result of the distance measuring sensor 212a and an image acquired from the camera 222 (hereinafter referred to as a camera image). Is different. Hereinafter, only the parts different from the third embodiment will be described, and the same parts as those in the third embodiment will be denoted by the same reference numerals and the description thereof will be omitted.

First, the external structure of the three-dimensional distance measuring apparatus 200 will be described.
The camera 222 faces the negative direction of the zrs axis, and can capture images of the feet and surroundings of the leg wheel type robot 100. As in the sensor coordinate system, the coordinate system of the camera 222 (hereinafter referred to as the camera coordinate system) has the same direction as the xrs axis, yrs axis, and zrs axis as the xca axis, yca axis, and zca axis, respectively. Have different origin positions. That is, the camera 222 is arranged so that the xrs-yrs plane in the sensor coordinate system and the xca-yca plane in the camera coordinate system are parallel. The xrs-zrs plane and the xca-zca plane, and the yrs-zrs plane and the yca-zca plane are also in a parallel relationship.

Next, the control structure of the three-dimensional distance measuring apparatus 200 will be described.
The sensing processor 210 further executes processing for recognizing the boundary of the continuous surface based on the measurement result of the distance measuring sensor 212a and the camera image.
Next, the principle of object recognition using the camera 222 and the three-dimensional distance measuring device 200 will be described.

FIG. 44 is a diagram for explaining the principle of object recognition using the camera 222 and the three-dimensional distance measuring apparatus 200.
First, as shown in FIG. 44, images of the feet and surroundings of the leg wheel type robot 100 are taken by the camera 222, and line segments are detected from the camera images.
Next, the boundary of the continuous surface is determined as a sensor feature point from the coordinates of the measurement point measured for each scanning plane by the three-dimensional distance measuring apparatus 200, and the sensor feature point is projected onto the camera image by coordinate conversion.

And the boundary of a continuous surface is recognized based on the positional relationship of the line segment detected from the camera image (henceforth a line segment of a camera image) and the projection point of a sensor feature point.
Accordingly, the recognition accuracy can be improved as compared with the case where the recognition is performed based only on the sensor feature points obtained by the three-dimensional distance measuring apparatus 200 and the case where the recognition is performed based only on the camera image.

Next, an object recognition process executed by the three-dimensional distance measuring apparatus 200 will be described.
FIG. 45 is a flowchart showing object recognition processing executed by the three-dimensional distance measuring apparatus 200.
When the object recognition process is executed in the sensing processor 210, the process first proceeds to step S150 as shown in FIG.

  In step S150, an image is acquired from the camera 222, the process proceeds to step S152, distortion correction processing is executed on the camera image, and the process proceeds to step S154, from which the distortion-corrected camera image is subjected to Sobel, Canny filter, and the like. In step S156, an edge extraction process for extracting edges is performed, and a line segment is detected from the camera image from which the edges have been extracted by Hough transform.

Subsequently, the process proceeds to step S224 through steps S200 to S220, and the coordinate information of the end point determined as the boundary of the continuous surface is converted into the sensor coordinate system, and the converted coordinate information is stored in the memory, and the process proceeds to step S226. To do.
In step S226, it is determined whether or not the processing of steps S202 to S224 has been completed for all scanning planes corresponding to the scanning angle range and scanning unit angle of the second scanning processing, and when it is determined that the processing has ended (Yes) ) Proceeds to step S228.

In step S228, based on the coordinate information stored in the memory, the end point determined as the boundary of the continuous surface is used as the sensor feature point, and the sensor feature point is projected onto the camera image by coordinate conversion.
FIG. 46 is a diagram illustrating a sensor coordinate system, a camera coordinate system, and a coordinate system of the image sensor surface of the camera 222.

Sensor feature points can be projected onto a camera image using a general pinhole model.
The coordinate system of the image sensor surface of the camera 222 is Σ cm, the relative position between the distance measuring sensor 212a and the camera 222 is r = (rx, ry, rz), the focal length of the lens of the camera 222 is f, and the effective pixel width of the image sensor Is W and the effective pixel height of the image sensor is H, P (xrs1, yrs1, zrs1) rs = (xrs1-rx, yrs1-ry, zrs1-rz) ca in the sensor coordinate system is shown in FIG. As shown in (b), the image can be projected onto a coordinate P ′ in the coordinate system of the imaging element surface. The coordinate P ′ can be obtained by the following equation (13).

  In FIG. 46 and the above equation (13), the coordinates (a, b, c) in the sensor coordinate system Σrs, the camera coordinate system Σca, and the coordinate system Σcm of the image sensor surface are respectively represented by (a, b, c) rs, (A, b, c) ca, (a, b, c) cm.

  Next, as shown in FIG. 45, the process proceeds to step S230, and in the camera image, for each line segment of the camera image, the line segment and the sensor feature points existing within a predetermined distance from the straight line obtained by extending the line segment. And the process moves to step S232 to group the line segments associated with the same sensor feature point, and the process moves to step S234 to determine the continuous surface based on the coordinates of the end points of the line segments belonging to the same group. Determine the boundary line.

FIG. 47 is a diagram for explaining a case in which line segments of camera images and sensor feature points are associated, grouped, and boundary lines are determined.
As shown in FIG. 47A, it is assumed that two line segments l1 and l2 having close inclinations are detected from the camera image, and four projection points P1 to P4 are obtained around the line segments l1 and l2. In this case, since projection points P2, P3, and P4 exist within a predetermined distance from a straight line obtained by extending the line segment l1, the projection points P2, P3, and P4 with respect to the line segment l1 as shown in FIG. Are associated. Further, since the projection points P1, P2, and P3 exist within a predetermined distance from the straight line obtained by extending the line segment l2, the projection points P1, P2, and P3 are associated with the line segment l2.

Next, since the projection points P2 and P3 are associated in common with the line segments l1 and l2, the line segments l1 and l2 are grouped as one group.
Then, based on the coordinates of the end points P5 and P6 of the line segment l1 and the end points P7 and P8 of the line segment l2 belonging to the same group, as shown in FIG. The determined straight line is determined as the boundary line of the continuous surface.

As a result, due to the influence of contrast or the like, even though a plurality of line segments should be detected from the camera image as actually one line segment, a plurality of line segments are set to 1 based on the correspondence with sensor feature points. It can be grouped as one line segment and the boundary line of the continuous surface can be determined.
Next, as shown in FIG. 45, the process proceeds to step S237, where boundary data is generated based on the information regarding the straight line determined as the boundary line of the continuous surface, and the process proceeds to step S239, where the hub 76 and the communication I / F 64 are processed. Then, the generated boundary data is output to the CPU 60, and the series of processes is terminated.

On the other hand, when it is determined in step S226 that the processes in steps S202 to S224 are not completed for all scanning planes (No), the process proceeds to step S202 via step S240.
Next, the elevation control process will be described.
FIG. 48 is a flowchart showing the elevation control process.

When the elevation control process is executed by the CPU 60, first, the process proceeds to step S301 as shown in FIG.
In step S301, boundary data is input from the three-dimensional distance measuring apparatus 200, and the process proceeds to step S302. Based on the input boundary data, the coordinates of the camera coordinate system are converted into the coordinates of the global coordinate system, and A point on the boundary line is detected as a feature point of the staircase.

Next, after steps S302 to S320, the process proceeds to step S322 to determine whether or not the leg tip has landed on the tread. When it is determined that the leg tip has landed (Yes), the series of processes is terminated. To return to the original process.
On the other hand, when it is determined in step S322 that the leg tip does not land (No), the process proceeds to step S312.

Next, the operation of the present embodiment will be described.
A case will be described in which a stairway exists on the movement path of the leg-wheel type robot 100 and the stairs are overcome. Since the third embodiment is different from the third embodiment in that the boundary of the continuous surface is recognized based on the measurement result of the distance measuring sensor 212a and the camera image, only different portions will be described.
FIG. 49 is a diagram illustrating the processing result of the camera image.

  In the sensing processor 210, first, an image is acquired from the camera 222 through step S150. For example, assume that an image as shown in FIG. Next, through step S152, distortion correction processing is performed on the camera image, and an image with corrected distortion is obtained as shown in FIG. Next, through step S154, edge extraction processing is executed on the camera image whose distortion has been corrected, and an image in which only edges are extracted is obtained as shown in FIG. Then, through step S156, a line segment is detected from the edge-extracted camera image. As a result, six line segments are obtained as shown in FIG.

Next, through steps S200 to S226, measurement results by the first scanning process are obtained for all scanning planes.
When the measurement is completed for all the scanning planes, the sensor feature points are projected onto the camera image through coordinate transformation based on the coordinate information stored in the memory through step S228.
FIG. 50 is a diagram illustrating the determination result of the continuous surface.

FIG. 51 is a diagram illustrating a result of projecting sensor feature points onto a camera image.
For the scanning plane φ0, as shown in FIG. 50, (1) the intersection of the region (φ0, 0) corresponding to the floor surface and the region (φ0, 1) corresponding to the first-stage kick plate, (2) The intersection of the region (φ0, 1) and the region (φ0, 2) corresponding to the first step plate, (3) the region (φ0, 2) and the region (φ0, 3) corresponding to the second step kick plate And four intersections of (4) the intersection of the region (φ0, 3) and the region (φ0, 4) corresponding to the second step board are determined as sensor feature points. Therefore, as shown in FIG. 51, these four sensor feature points are projected on the camera image as projection points on the scanning plane φ0 that extends from the upper right to the lower left of the center.

  For the scanning plane φ1, as shown in FIG. 50, (1) the intersection of the region (φ1, 0) corresponding to the floor surface and the region (φ1, 1) corresponding to the first-stage kick plate, (2) The intersection of the region (φ1, 1) and the region (φ1, 2) corresponding to the first step board, (3) the region (φ1, 2) and the region (φ1, 3) corresponding to the second step kick plate And four intersections of (4) the intersection of the region (φ1, 3) and the region (φ1, 4) corresponding to the second step board are determined as sensor feature points. Therefore, as shown in FIG. 51, these four sensor feature points are projected onto the camera image as projection points on the scanning plane φ1 that goes from the center right above to the center right.

  For the scanning plane φ2, as shown in FIG. 50, (1) the intersection of the region (φ2, 0) corresponding to the floor surface and the region (φ2, 1) corresponding to the first-stage kick plate, (2) The intersection of the region (φ2, 1) and the region (φ2, 2) corresponding to the first step plate, (3) The region (φ2, 2) and the region (φ2, 3) corresponding to the second step kick plate And four intersections of (4) the intersection of the area (φ2, 3) and the area (φ2, 4) corresponding to the second step board are determined as sensor feature points. Accordingly, as shown in FIG. 51, these four sensor feature points are projected onto the camera image as projection points on the scanning plane φ2 that extends from the upper left center to the lower right center.

  Next, through steps S230 to S234, in the camera image, the line segment of the camera image is associated with the sensor feature point, the line segments associated with the same sensor feature point are grouped, and the line segment belonging to the same group The boundary line of the continuous surface is determined by linear approximation based on the coordinates of the end points. In the example of FIG. 51, two straight lines are determined as the boundary line of the continuous surface from the positional relationship between the line segment of the camera image and each projection point.

Then, through steps S237 and S239, boundary data is generated based on information about the straight line determined as the boundary line of the continuous surface, and the generated boundary data is output to the CPU 60.
When the boundary data is input, the CPU 60 detects the feature point of the staircase based on the input boundary data through step S302. Further, the input boundary data is analyzed, and for example, a continuous surface having an inclination close to 0 is regarded as a horizontal surface, and it is determined that the leg-wheel type robot 100 is a surface on which walking is possible.

  Thus, in this embodiment, the distance measuring sensor 212a that measures the distance to the measurement point on the object, and the camera 222 that captures an image including the measurement point that can be measured in the scanning range of the distance measuring sensor 212a. The distance measurement sensor 212a is scanned, the measurement result of the distance measurement sensor 212a is obtained for the measurement points that can be measured in the scanning range, the sensor feature point is detected based on the obtained measurement result, and the image is taken from the camera 222. , The line segment is detected from the camera image, and the boundary of the continuous surface is recognized based on the line segment of the detected camera image and the sensor feature point.

  Thereby, in addition to the distance measurement sensor 212a, a feature on the object is detected using a camera 222 of a different system, and the boundary of the continuous surface is recognized based on the two detection results. The shortcomings of the system based on 212a can be compensated for by the system based on the camera 222, and the possibility of a decrease in recognition accuracy can be reduced when object recognition is performed by the two-dimensional distance measuring device 212 using the distance measuring sensor 212a. . In addition, since it is not necessary to increase the number of scans in the second scanning process, the measurement time can be shortened.

Further, in the present embodiment, the distance measurement sensor 212a is scanned, the measurement result of the distance measurement sensor 212a is obtained for the measurement points that can be measured in the scanning range, and the obtained measurement result is converted into the coordinates of the orthogonal coordinate system. The line segment in the orthogonal coordinate system is detected by the Hough transform based on the converted coordinates of at least two measurement points, and the sensor feature point is detected based on the detected line segment.
This makes it possible to grasp at least the planar shape of an object as a boundary between continuous surfaces, which is suitable for posture control of robots that require complex posture control, such as legged robots and leg-wheel type robots 100. A recognition result can be obtained. Further, since the line segment is detected by the Hough transform, when the object recognition is performed by the two-dimensional distance measuring device 212 using the distance measuring sensor 212a, there is a possibility that the recognition accuracy may be lowered due to a decrease in measurement resolution or a variation in measurement results. Can be reduced.

Furthermore, as compared with the least square method, robust detection can be performed for an edge that is difficult to detect.
Furthermore, in this embodiment, sensor feature points are detected based on the coordinates of the end points of the detected line segment.
Thereby, the boundary of a continuous surface can be recognized comparatively correctly.

Furthermore, in this embodiment, a line segment is detected from the camera image, and the boundary of the continuous surface is recognized in the camera image based on the positional relationship between the line segment of the camera image and the sensor feature point.
Thereby, possibility that recognition accuracy will fall can further be reduced.
Furthermore, in this embodiment, for each line segment of the camera image, the line segment is associated with a sensor feature point existing within a predetermined distance from a straight line obtained by extending the line segment, and the same sensor feature point corresponds The attached line segments are grouped, and the boundary line of the continuous surface is determined based on the coordinates of the end points of the line segments belonging to the same group.

As a result, due to the influence of contrast or the like, even though a plurality of line segments should be detected from the camera image as actually one line segment, a plurality of line segments are set to 1 based on the correspondence with sensor feature points. Since it is grouped as one line segment and the boundary line of the continuous surface is determined, the possibility that the recognition accuracy is lowered can be further reduced.
In the fifth embodiment, the camera 222 corresponds to the imaging means of the invention 17, 24 or 26, and the yrs' axis rotation mechanism is the first scanning means of the invention 21 or 22, or the first rotation of the invention 22. The zrs axis rotation mechanism corresponds to the second scanning means of the invention 21 or 22, or the second rotation means of the invention 22. Step S150 corresponds to the imaging step of the invention 29, steps S152 to S156 correspond to the second feature detection means of the invention 17, 18 or 24, or the second feature detection step of the invention 29, and step S156 This corresponds to the image line segment detecting means of the invention 24 or 25.

In the fifth embodiment, steps S206, S210, and S220 correspond to the first feature detection means of the invention 17, 18, or 24, or the first feature detection step of the invention 29, and steps S202 and S240 are This corresponds to the measurement result acquisition means of the invention 17, 18, 21, 22, or 24, or the measurement result acquisition step of the invention 29. Step S206 corresponds to the coordinate conversion means of the invention 18, step S210 corresponds to the line segment detection means of the invention 18, and step S234 is the recognition means of the invention 17, 18, 24 or 25, or the invention 29. This corresponds to the recognition step.
In the fifth embodiment, the yrs ′ axis corresponds to the first scanning axis of the invention 22 and the zrs axis corresponds to the second scanning axis of the invention 22.

[Sixth Embodiment]
Next, a sixth embodiment of the present invention will be described with reference to the drawings. FIG. 52 is a diagram showing a sixth embodiment of the leg-wheel robot, object recognition apparatus, and object recognition method according to the present invention.

This embodiment is different from the fifth embodiment in that the Hough transform is performed after connecting the measurement points with line segments in the orthogonal coordinate system. Hereinafter, only the parts different from the fifth embodiment will be described, and the same parts as those in the fifth embodiment will be denoted by the same reference numerals and the description thereof will be omitted.
First, an object recognition process executed by the three-dimensional distance measuring apparatus 200 will be described.

FIG. 52 is a flowchart showing object recognition processing executed by the three-dimensional distance measuring apparatus 200.
When the object recognition process is executed in the sensing processor 210, as shown in FIG. 52, the process proceeds to step S208 via steps S150 to S206.
In step S208, the measurement points adjacent in the x-axis direction in the scanning plane coordinate system are connected by line segments based on the coordinate information converted in step S206, and the process proceeds to step S210. A line segment in the orthogonal coordinate system is detected by Hough transform based on the coordinate information of the point.

Then, after steps S220 and S224, the process proceeds to step S226 to determine whether or not the processing of steps S202 to S224 has been completed for all the scanning planes, and when it is determined that the processing has been completed (Yes) Through steps S228 to S239, the series of processes is terminated.
On the other hand, when it is determined in step S226 that the processes in steps S202 to S224 are not completed for all scanning planes (No), the process proceeds to step S202 via step S240.

Next, the operation of the present embodiment will be described.
A case will be described in which a stairway exists on the movement path of the leg-wheel type robot 100 and the stairs are overcome. Since the fifth embodiment is different from the fifth embodiment in that a line segment is detected by Hough transform, only different portions will be described.
Through steps S208 and S210, measurement points are connected by line segments based on the converted coordinate information, and line segments in the orthogonal coordinate system are detected by Hough transform based on the coordinate information of the points on the obtained line. .

  In the orthogonal coordinate system, each measurement point is represented as a set of a plurality of points along the contours of the kick board and the tread board as shown in FIG. In the example of FIG. 43 (a), in the region corresponding to the first step tread, some measurement points are distributed in a region deviating from the continuous surface. The measurement results vary due to the influence of the error area A1. The area A2 has a lower measurement resolution than the other areas.

When a line segment connection is made for this measurement result, each measurement point is connected by one line as shown in FIG. As a result, between the measurement points where no measurement point exists, the points on the line are interpolated.
When the Hough transform is performed on the connection result, as shown in FIG. 43 (c), a line segment along the outline of each kick board and each tread board is detected.

If the Hough transform is performed on the measurement result in FIG. 43A without connecting the line segments, as shown in FIG. 40B, the line segments along the contours of the treads are detected. The line segment along each kick plate cannot be detected.
As described above, in this embodiment, the distance measuring sensor 212a that measures the distance to the measurement point on the object is provided, the distance measurement sensor 212a is scanned, and the distance measurement sensor can be measured for the measurement points that can be measured in the scanning range. The measurement result of 212a is acquired, the acquired measurement result is converted into coordinates in an orthogonal coordinate system, the converted measurement points are connected by line segments, and orthogonality is obtained by Hough transform based on the coordinates of the points on the obtained line A line segment in the coordinate system is detected, and the boundary of the continuous surface is recognized based on the detected line segment.

  This makes it possible to grasp at least the planar shape of an object as a boundary between continuous surfaces, which is suitable for posture control of robots that require complex posture control, such as legged robots and leg-wheel type robots 100. A recognition result can be obtained. Further, since the line segment is detected by the Hough transform, when the object recognition is performed by the two-dimensional distance measuring device 212 using the distance measuring sensor 212a, there is a possibility that the recognition accuracy may be lowered due to a decrease in measurement resolution or a variation in measurement results. Can be reduced. In addition, since line segments are detected based on the coordinates of points on the line obtained by connecting the measurement points with line segments, relatively accurate recognition results can be obtained even if measurement resolution decreases or measurement results vary. The possibility that the recognition accuracy is lowered can be further reduced.

Furthermore, as compared with the least square method, robust detection can be performed for an edge that is difficult to detect.
In the sixth embodiment, steps S152 to S156 correspond to the second feature detection means of the invention 19, steps S206 to S210, S220 correspond to the first feature detection means of the invention 19, and steps S202, S240 corresponds to the measurement result acquisition means of the nineteenth aspect. Further, step S206 corresponds to the coordinate conversion means of the invention 19, step S208 corresponds to the inter-measurement point interpolation means of the invention 19, step S210 corresponds to the line segment detection means of the invention 19, and step S234 is executed. This corresponds to the recognition means of the nineteenth aspect.

[Seventh Embodiment]
Next, a seventh embodiment of the present invention will be described with reference to the drawings. 53 to 56 are views showing a seventh embodiment of the leg-wheel type robot, the object recognition apparatus, and the object recognition method according to the present invention.

  Compared to the fifth embodiment, the present embodiment calculates the inclination at each measurement point in the orthogonal coordinate system, calculates the appearance frequency of each inclination, the calculated appearance frequency and the coordinates of each measurement point The point of recognizing the boundary of the continuous surface is different. Hereinafter, only the parts different from the fifth embodiment will be described, and the same parts as those in the fifth embodiment will be denoted by the same reference numerals and the description thereof will be omitted.

First, an object recognition process executed by the three-dimensional distance measuring apparatus 200 will be described.
FIG. 53 is a flowchart showing object recognition processing executed by the three-dimensional distance measuring apparatus 200.
When the object recognition process is executed in the sensing processor 210, the process proceeds to step S408 via steps S150 to S206 as shown in FIG.

In step S408, the inclination at each measurement point in the orthogonal coordinate system is calculated based on the coordinate information converted in step S206.
FIG. 54 is a diagram illustrating an example of calculating the inclination. In the figure, the x-axis and z-axis indicate axes in the scanning plane coordinate system, and are separate from the axes in the sensor coordinate system and the camera coordinate system.
The inclination at the measurement point is shown in FIG. 54A based on the coordinates of the measurement point and the coordinates of a predetermined number of measurement points adjacent in the x-axis direction for each measurement point in the scanning plane coordinate system. As shown, it can be calculated by the least square method.

As shown in FIG. 54 (a), a regression line is approximated to a predetermined number of measurement points before and after the measurement points (white circles in FIG. 54 (a)) to be calculated by the least square method. The inclination is the inclination at the target measurement point. The least squares method is less affected by data variations but has a relatively large amount of calculation.
As another method, for each measurement point, an inclination can be calculated based on a difference value between coordinates of two measurement points before and after a predetermined number of other measurement points.

As shown in FIG. 54 (b), the first difference value that is the difference value between the z coordinates of the two measurement points before and after (for example, if the z coordinate of the measurement point of interest is z _i , z _{i + 2} −z _{i -2)} calculates the second difference value is a difference value between the x-coordinate of the front and rear two measurement points (e.g., the x-coordinate of the measurement point of interest When _{x i, x i + 2 -x} i-2 ) And the inclination (first difference value / second difference value) at the measurement point of interest is obtained from these calculation results. In this method, the influence of data variation is greater than that in the least squares method, but since the calculation requires only simple subtraction and division, the slope can be calculated faster than in the least squares method.

Next, as shown in FIG. 53, the process proceeds to step S410, and the appearance frequency of each inclination with respect to the total number of inclinations calculated in step S408 is calculated. For example, the number of measurement points at each inclination with respect to the total number of measurement points is calculated as the appearance frequency.
Next, the process proceeds to step S412, where the appearance frequency of the unprocessed slope is selected from the appearance frequencies of the respective slopes calculated in step S410, and the process proceeds to step S414, where the selected appearance frequency and a preset threshold value are selected. Are compared, and it is determined whether or not the selected appearance frequency is equal to or higher than the threshold. If it is determined that the selected appearance frequency is equal to or higher than the threshold (Yes), the process proceeds to step S416.

In step S416, based on the coordinate information of the measurement points having the inclination related to the selected appearance frequency and the inclination of the predetermined range, it is determined that the region including the measurement points having continuous coordinates is a continuous surface. In a region determined to be a continuous surface, a measurement point whose inclination changes abruptly is determined as a boundary of the continuous surface.
Next, the process proceeds to step S418, where the coordinate information of the measurement point determined as the boundary of the continuous surface is converted into the sensor coordinate system, the converted coordinate information is stored in the memory, and the process proceeds to step S420.

In step S420, it is determined whether or not the processes in steps S414 to S418 and S434 have been completed for all inclinations. If it is determined that the process has been completed (Yes), the process proceeds to step S226.
In step S226, it is determined whether or not the processing in steps S202 to S420 has been completed for all the scanning planes. When it is determined that the processing has been completed (Yes), the series of processing is completed through steps S228 to S239. To do.

On the other hand, when it is determined in step S226 that the processes in steps S202 to S420 are not completed for all scanning planes (No), the process proceeds to step S202 via step S240.
On the other hand, when it is determined in step S420 that the processes in steps S414 to S418 and S434 are not completed for all inclinations (No), the process proceeds to step S412.

On the other hand, when it is determined in step S414 that the selected appearance frequency is less than the threshold (No), the process proceeds to step S434, and the coordinate information of the measurement point having the slope related to the selected appearance frequency is excluded as measurement noise. Then, the process proceeds to step S420.
Next, the operation of the present embodiment will be described.
A case will be described in which a stairway exists on the movement path of the leg-wheel type robot 100 and the stairs are overcome. Since the fifth embodiment is different from the fifth embodiment in that the boundary of the continuous surface is determined based on the appearance frequency of the inclination, only different portions will be described.

First, through step S408, the inclination at each measurement point is calculated based on the converted coordinate information.
FIG. 55 is a diagram illustrating an example of inclinations in the x-axis direction and the z-axis direction calculated by the least square method.
Here, the slope at each measurement point is calculated by the least square method. Here, when the least square method is used, as shown in FIGS. 55 (a) and 55 (b), the inclination in the x-axis direction and the z-axis direction with respect to a plurality of measurement points to which the least square method is applied. May be different from the slope. Therefore, as shown in the following equations (14) and (15), the least square method calculation is performed using two linear equations for obtaining the inclinations in the x-axis direction and the z-axis direction.

z = a _x · x + b _x (14)
x = _az , z + _bz (15)

Then, a _x and b _x in the above equation (14) are calculated by the following equation (16), and a _z and b _z in the above equation (15) are calculated by the following equation (17).

When a _x and b _x and a _z and b _z are calculated, the distance between the straight line of the above formulas (14) and (15) and the respective measurement points used for the least square calculation is calculated. While calculating as the residuals h _x and h _z , the sum of squares of the residuals h _{x and} the square of the residuals h _z for the respective measurement points are calculated (the following formula (18)).

When the square sum of the residual h _{x and} the square sum of the residual h _z are calculated, the straight line with the smaller value is compared as the correct straight line, and the calculation target is calculated based on the slope of this straight line. Find the slope at the measurement point. Specifically, _if the square sum of the residual h _x is smaller, “a = a _x , b = b _x ”. _If the square sum of the residual h _z is smaller, “a = 1 / _az”. , B = 1 / b _z ”.

  Next, through steps S410 to S414, the appearance frequency of each inclination is calculated, the appearance frequency of the undetermined inclination is selected, and it is determined whether or not the selected appearance frequency is equal to or greater than a threshold value. At this time, if it is equal to or greater than the threshold value, the boundary of the continuous surface is determined through step S416 based on the selected inclination of the appearance frequency and the coordinate information of the measurement point having the predetermined range of inclination.

FIG. 56 is a diagram showing an example of the appearance frequency of the inclination with respect to a certain scanning plane.
For example, it is assumed that the appearance frequency as shown in FIG. 56 is obtained. In the example of FIG. 56, when the frequency of appearance near the inclination is relatively high and the coordinates of the measurement points having these inclinations are continuous, the region including the continuous measurement points is a continuous surface. It is determined. On the movement path of the leg-wheel type robot 100, there is a staircase having a constant step and a tread plate as a continuous surface. Therefore, the horizontal plane corresponding to the tread plate has a series of measurement points with zero inclination and substantially zero. Appear as coordinates. In this case, it can be estimated that there is a horizontal plane there.

  And in the area | region determined to be a continuous surface, the measurement point in which inclination changes rapidly is determined as a boundary of a continuous surface. In the example of FIG. 50, for a certain scanning plane, (1) an intersection of an area corresponding to the floor surface and an area corresponding to the first-stage kick board, (2) an area corresponding to the area and the first-stage tread board, and The four intersections of the intersection of (3) the area and the area corresponding to the second-stage kick board, and (4) the intersection of the area and the area corresponding to the second-stage tread are Determined.

Next, through step S418, the coordinate information of the measurement point determined as the boundary of the continuous surface is converted into the sensor coordinate system, and the converted coordinate information is stored in the memory.
On the other hand, if it is less than the threshold value, the coordinate information of the measurement point is excluded as measurement noise through step S434.
The processes in steps S414 to S418 and S434 are performed for all inclinations.

  As described above, in this embodiment, the distance measuring sensor 212a that measures the distance to the measurement point on the object is provided, the distance measurement sensor 212a is scanned, and the distance measurement sensor can be measured for the measurement points that can be measured in the scanning range. The measurement result of 212a is acquired, the acquired measurement result is converted into the coordinates of the orthogonal coordinate system, and for each converted measurement point, the orthogonal coordinate system is based on the coordinates of the measurement point and the coordinates of the surrounding measurement points. The slope at the measurement point is calculated, the appearance frequency of each slope with respect to the calculated total number of slopes is calculated, and the boundary of the continuous surface is recognized based on the calculated appearance frequency and the converted coordinates of each measurement point.

  This makes it possible to grasp at least the planar shape of an object as a boundary between continuous surfaces, which is suitable for posture control of robots that require complex posture control, such as legged robots and leg-wheel type robots 100. A recognition result can be obtained. Further, since the boundary of the continuous surface is recognized based on the appearance frequency of the inclination at the measurement point and the coordinates of each measurement point, the recognition is performed when the object is recognized by the two-dimensional distance measuring device 212 using the distance measuring sensor 212a. The possibility that the accuracy is lowered can be reduced.

  In the seventh embodiment, steps S152 to S156 correspond to the second feature detection means of the invention 20, steps S206 and S408 to S416 correspond to the first feature detection means of the invention 20, and steps S202, S240 corresponds to the measurement result acquisition means of the twentieth aspect. Step S206 corresponds to the coordinate transformation means of the invention 20, step S408 corresponds to the inclination calculation means of the invention 20, step S410 corresponds to the appearance frequency calculation means of the invention 20, and step S234 corresponds to the invention. This corresponds to 20 recognition means.

In the third and fourth embodiments, the configuration is such that the continuous surface on the object or the boundary of the continuous surface is recognized. However, the present invention is not limited to this. It can also be configured to recognize.
In the fourth and sixth embodiments, adjacent measurement points are connected by line segments. However, the present invention is not limited to this, and the measurement points may be measured by straight lines, multi-degree curves or other curves. May be connected, or the measurement points may be approximated by a straight line, a line segment, a multi-order curve, or other curves. In this case, the measurement points do not necessarily have to be located on the line, and adjacent measurement points need not be targeted.

In the fourth and sixth embodiments, the line segment is detected by the Hough transform based on the coordinates of the points on the line obtained by the line segment connection. However, the present invention is not limited to this. A line segment may be detected by Hough transform based on the coordinates of a point existing within a predetermined distance from the given line.
In the fifth to seventh embodiments, the three-dimensional distance measuring device 200 rotates the distance measuring sensor 212a around the yrs' axis and rotates the two-dimensional distance measuring device 212 around the zrs axis. However, the present invention is not limited to this, and includes a plurality of distance measuring sensors 212a and a plurality of rotation mechanisms that respectively rotate the distance measuring sensors 212a around a scanning axis orthogonal to the measurement direction of the distance measuring sensor 212a. The distance measuring sensor 212a may be arranged around the zrs axis.

As a result, as in the fifth to seventh embodiments, the three-dimensional shape of the object can be grasped as the boundary of the continuous surface, so that it is complicated as in the legged robot and the leg wheel type robot 100. A recognition result suitable for posture control of a robot that requires posture control can be obtained.
In the fifth to seventh embodiments, the line segment is detected from the camera image by the Hough transform. However, the present invention is not limited to this, and the line segment is detected by the following detection method. It can also be configured.

As a first detection method, the edge extraction process is executed a plurality of times while changing the parameters of the edge extraction process, and a line segment is detected by Hough transform from each edge-extracted camera image. And the boundary of a continuous surface is recognized based on all the detected line segments. Thereby, possibility that recognition accuracy will fall can further be reduced.
As a second detection method, a plurality of images are acquired from the camera 222 by changing the shooting conditions of the camera 222 such as a shutter speed and an aperture, and distortion correction processing and edge extraction processing are respectively performed on the camera images. A line segment is detected by Hough transform from each camera image obtained by edge extraction. And the boundary of a continuous surface is recognized based on all the detected line segments. Thereby, possibility that recognition accuracy will fall can further be reduced.

In the fifth to seventh embodiments, the boundary of the continuous surface on the object is recognized. However, the present invention is not limited to this, and the continuous surface, intermittent surface, and other surfaces on the object, or their boundaries. It can also be configured to recognize.
In the fifth to seventh embodiments, the boundary data is generated on the basis of the information about the straight line determined as the boundary line of the continuous surface. It can also be configured to generate the surface data based on the information regarding the straight line determined as the boundary line and the coordinate information of the sensor feature point.

  Since the line segment connecting the sensor feature points determined as the boundary of the continuous surface is an intersection line where the continuous surface and the scanning plane intersect, generation of the surface data includes, for example, a line segment connecting the sensor feature points in a certain scanning plane, In the scanning plane adjacent to the z-axis, those having inclinations and coordinates with a line segment connecting sensor feature points within a predetermined range are determined as continuous surfaces, and correspond to the straight line determined as the boundary line between these line segments and the continuous surface. This is performed by associating coordinate information or connecting them using a known interpolation method. For example, since a continuous surface having an inclination close to 0 can be regarded as a horizontal surface, it can be determined that the surface is a walking surface.

  In the fifth to seventh embodiments, the sensor feature points are projected onto the camera image by coordinate transformation. However, the present invention is not limited to this, and the line segment of the camera image is represented by a plane in the scanning plane coordinate system. The sensor feature point and the line segment of the camera image may be projected onto a plane or space of another coordinate system. That is, the coordinate system for determining the positional relationship between the line segment of the camera image and the sensor feature point can be arbitrary.

  In the fifth to seventh embodiments, the line segment is detected from the camera image and the boundary of the continuous surface is recognized based on the detected line segment. However, the present invention is not limited to this. Detect points, straight lines, multi-dimensional curves, circles, ellipses and other curves, planes, curved surfaces and other surfaces, cubes, spheres and other three-dimensional features from the camera image, and continuous surfaces based on the detected features It is also possible to configure so as to recognize the boundary.

  In the fifth to seventh embodiments, the sensor feature point is detected based on the measurement result of the distance measuring sensor 212a, and the boundary of the continuous surface is recognized based on the detected sensor feature point. However, the present invention is not limited to this, and straight lines, line segments, multi-order curves, circles, ellipses and other curves, planes, curved surfaces and other surfaces, cubes, spheres, and other three-dimensional features that indicate features on the object are detected and detected. The boundary of the continuous surface can be recognized based on the feature.

  In the fifth to seventh embodiments, the camera 222 is arranged so that the xrs-yrs plane in the sensor coordinate system and the xca-yca plane in the camera coordinate system are parallel to each other. However, the present invention is not limited to this. First, if an image including a measurement point that can be measured within the scanning range of the distance measuring sensor 212a can be taken, the image can be arranged at an arbitrary position and orientation with respect to the distance measuring sensor 212a.

In the third to seventh embodiments, the encoder 218 is provided on the drive rotary shaft. However, the present invention is not limited to this, and the encoder 218 may be provided on the driven rotary shaft.
Thereby, the scanning angle in the second scanning process can be detected with high accuracy without being affected by the transmission error.
In the third to seventh embodiments, the rotational driving force of the drive rotating shaft is transmitted to the driven rotating shaft via the pulleys 220a and 220b and the belt 221. Not limited to this, the configuration may be such that the rotational driving force of the drive rotary shaft is transmitted to the driven rotary shaft via a plurality of gears.

  In the third to seventh embodiments, the distance information is acquired in the first scanning process discretely (distance information is acquired in the first scanning process after being rotated in the second scanning process). However, the present invention is not limited to this, and the configuration is such that the scanning angle and the measurement distance are associated with each other continuously (distance information is acquired by the first scanning process while being rotated by the second scanning process). You can also.

In the third to seventh embodiments, the scanning angle range and the scanning unit angle are set based on the command signal from the CPU 60. However, the present invention is not limited to this, and the three-dimensional distance measurement is performed. A configuration in which the apparatus 200 is set in advance may be employed.
In the third to seventh embodiments, the three-dimensional distance measuring device 200 rotates the distance measuring sensor 212a around the yrs' axis and rotates the two-dimensional distance measuring device 212 around the zrs axis. However, the present invention is not limited to this, and the distance measuring sensor 212a may be rotated about the zrs axis, and the two-dimensional distance measuring device 212 may be rotated about the yrs' axis. Further, not only about the yrs ′ axis and the zrs axis, but any two axes that are orthogonal to the measurement direction of the distance measuring sensor 212a may be used. Further, not limited to such a rotation mechanism, the distance measuring sensor 212a is moved in a first scanning direction that is different from the measuring direction of the distance measuring sensor 212a, and the measuring direction of the distance measuring sensor 212a is different from the first scanning direction. It can also be configured as a moving mechanism so as to move the distance measuring sensor 212a in two scanning directions. In this case, as the shape of the movement path, a circular arc or other curve can be adopted in addition to a straight line. A combination of a rotating mechanism and a moving mechanism can also be used.

Such a configuration change can be similarly applied to the above-described configuration including the plurality of distance measuring sensors 212a and the rotation mechanism.
In the fifth to seventh embodiments, the two-dimensional distance measuring device 212 itself is rotated as shown in FIG. 57 (a). However, the present invention is not limited to this, and an optical distance measuring sensor is used. As shown in FIG. 57B, a mirror inserted on the optical axis in the measurement direction may be rotated.

FIG. 57 is a diagram showing a configuration when the measurement direction of the distance measuring sensor is changed.
Moreover, although the said 3rd thru | or 7th embodiment was demonstrated as an independent embodiment, the said 3rd thru | or 7th embodiment is applied with respect to the said 1st or 2nd embodiment. You can also
In the third to seventh embodiments, the leg-wheel type robot, the object recognition apparatus, and the object recognition method according to the present invention are applied to the case of going over stairs. The same applies to the case of overcoming the step.

  In the third to seventh embodiments, the leg-wheel type robot, the object recognition apparatus, and the object recognition method according to the present invention are applied to the leg-wheel type robot 100. However, the present invention is not limited to this. The present invention can be applied to other cases without departing from the spirit of the invention. For example, the present invention can be applied to a leg-wheel type robot that realizes a leg structure with a linear motion joint, a robot having another configuration, a vehicle, and other devices. Further, by combining with a means for transmitting recognition information, development to a device and a recognition method as a means for a visually impaired person to recognize the outside world is also conceivable.

1 is a front view of a leg wheel type robot 100. FIG. 1 is a side view of a leg wheel type robot 100. FIG. It is a figure which shows the structure of the obstruction sensors 34 and 36. FIG. It is a figure which shows the attachment structure of the in-plane scanning leg tip sensor 38, Comprising: It is a front view of the leg part 12. FIG. It is a figure which shows the attachment structure of the in-plane scanning leg tip sensor 38, Comprising: It is a side view of the leg part 12. FIG. 2 is a block diagram showing a movement control system of a leg wheel type robot 100. FIG. It is a flowchart which shows a raising / lowering control process. It is a figure for demonstrating the principle of a light cutting method. It is a figure which shows the state which irradiated the laser beam to the staircase, and the image of the image pick-up element of the camera. It is a figure which shows the case where a two-dimensional shape measurement is performed by the in-plane scanning leg tip sensor 38. It is a figure which shows the coordinate system and global (world) coordinate system of the scanning leg tip sensor 38 in a plane. It is a figure which shows the case where the in-plane scanning leg tip sensor 38 is provided so that two-axis rotation is possible. It is a figure which shows the case where the leg part 12 is rotated around a yaw axis and moved at the time of raising / lowering control. It is a figure which shows the case where the measurement data of the scanning leg tip sensor 38 in a plane are converted into the orthogonal coordinate on a sensor measurement plane. It is a figure which shows the case where traveling control of the leg wheel type robot 100 is performed. It is a figure which shows the case where the in-plane scanning leg tip sensor 38 is provided inclining the predetermined angle α around the yaw axis with respect to the leg portion 12. It is a figure which shows the structure in the case of changing the measurement direction of a ranging sensor. (A) And (b) is a figure which shows the attitude | position at the time of wheel running movement of the leg wheel type robot 100. FIG. It is a figure which shows the example of a driving | running | working state of the leg wheel type robot 100 at the time of non-change driving control. FIGS. 7A and 7B are diagrams illustrating a traveling state of the leg-wheel type robot 100 during super turn control when the coordinates (0, 0) and the coordinates (xc, yc) of the base body 10 are used as the rotation center. is there. (A) And (b) is a figure which shows an example of the driving | running route of the leg wheel type robot 100. FIG. It is a figure which shows an example of the gravity center position of a robot. 1 is a front view of a leg wheel type robot 100. FIG. 1 is a side view of a leg wheel type robot 100. FIG. It is a front view (yrs-zrs plane) of the three-dimensional distance measuring apparatus 200. It is a side view (xrs-zrs plane) of the three-dimensional distance measuring apparatus 200. It is a top view (yrs-xrs plane) of the three-dimensional distance measuring apparatus 200. It is a figure which shows the scanning range of a ranging sensor. 2 is a block diagram showing a movement control system of a leg wheel type robot 100. FIG. It is a block diagram which shows the control structure of the two-dimensional distance measuring apparatus 212. 3 is a block diagram showing a control structure of a three-dimensional distance measuring apparatus 200. FIG. It is a figure for demonstrating the principle of the distance measurement of the two-dimensional distance measuring apparatus 212. FIG. It is a figure which shows the case where it scans by the 1st scanning process and the 2nd scanning process. It is a figure which shows the example of a distance measurement of the three-dimensional distance measuring apparatus 200. FIG. 5 is a flowchart showing object recognition processing executed by the three-dimensional distance measuring apparatus 200. It is a figure for demonstrating the principle of Hough conversion. It is a flowchart which shows a raising / lowering control process. It is a graph which shows the measurement result by the 1st scanning process. It is a graph which shows the result of having converted the distance information of the rotation coordinate system of each measurement point of FIG. 38 into the coordinate information of a rectangular coordinate system. It is a graph which shows the measurement point in a rectangular coordinate system, and the result of Hough transform. It is a figure which shows the determination result of a continuous surface. 4 is a flowchart showing object recognition processing executed by the three-dimensional distance measuring apparatus 200. It is a graph which shows the measurement point in a rectangular coordinate system, the result of line segment connection, and the result of Hough transform. It is a figure for demonstrating the principle of the object recognition using the camera 222 and the three-dimensional distance measuring apparatus 200. FIG. 4 is a flowchart showing object recognition processing executed by the three-dimensional distance measuring apparatus 200. 2 is a diagram illustrating a sensor coordinate system, a camera coordinate system, and a coordinate system of an image sensor surface of a camera 222. FIG. It is a figure for demonstrating the case where the matching of the segment of a camera image and a sensor feature point, grouping, and the determination of a boundary line are performed. It is a flowchart which shows a raising / lowering control process. It is a figure which shows the processing result of a camera image. It is a figure which shows the determination result of a continuous surface. It is a figure which shows the projection result to the camera image of a sensor feature point. 4 is a flowchart showing object recognition processing executed by the three-dimensional distance measuring apparatus 200. 4 is a flowchart showing object recognition processing executed by the three-dimensional distance measuring apparatus 200. It is a figure which shows the example of calculation of inclination. It is a figure which shows an example of the inclination of the x-axis direction computed by the least square method, and az-axis direction. It is a figure which shows an example of the appearance frequency of the inclination with respect to a certain scanning plane. It is a figure which shows the structure in the case of changing the measurement direction of a ranging sensor.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Leg wheel type robot 10 Base body 12 Leg parts 14-18 Rotary joint 20 Driving wheel 22, 24 Leg tip sensor 26 Horizontal laser 28, 30 Vertical laser 34, 36 Obstacle sensor 40, 50, 82 Motor 42, 52, 88 Encoder 44, 54, 90 Driver 70 Three-axis attitude sensor 80 Reducer 200 Three-dimensional distance measurement device 204 Lower support plate 206 Upper support plate 208 Camera support plate 210 Sensing processor 212 Two-dimensional distance measurement device 212a Distance sensor 212c, 216 Motor 212d, 218 Encoder 212b, 214 Driver 220a, 220b Pulley 221 Belt 222, 32 Camera

Claims (8)

A leg-wheel type robot comprising: a base; a leg connected to the base with a degree of freedom; and a wheel rotatably provided on the leg. ,
A distance measuring sensor rotatably provided on the leg so that a measurement direction thereof is relatively displaced with respect to the leg, an actuator that applies power for rotating the distance sensor, and the measurement A leg-wheel type robot comprising obstacle recognition means for recognizing an obstacle based on measurement results measured at different rotation angles by a distance sensor. In claim 1,
The leg portion is formed by connecting a plurality of links via joints,
The leg-wheel type robot according to claim 1, wherein the distance measuring sensor is provided on a link closest to a leg tip among the links of the leg portions. In any one of Claim 1 and 2,
The leg wheel type robot characterized in that the actuator rotates the distance measuring sensor only in one direction. In any one of Claim 1 and 2,
The leg wheel type robot, wherein the actuator rotates the distance measuring sensor in a forward direction and a reverse direction. In any one of Claims 1 thru | or 4,
And a second actuator for applying power for driving the leg or the wheel, and a control means for controlling the second actuator based on a recognition result of the obstacle recognition means,
The leg wheel type robot characterized in that the control means starts driving control of the second actuator after completion of measurement by the distance measuring sensor. In any one of Claims 1 thru | or 4,
And a second actuator for applying power for driving the leg or the wheel, and a control means for controlling the second actuator based on a recognition result of the obstacle recognition means,
The leg wheel type robot, wherein the control means starts driving control of the second actuator during measurement by the distance measuring sensor. In any one of Claims 1 thru | or 6,
The distance measuring sensor is provided on one or both of an inner surface facing the inside of the base of the leg and an outer surface facing the outside of the base of the leg. robot. In any one of Claims 1 thru | or 7,
The leg-wheel type robot according to claim 1, wherein the distance measuring sensor is provided to be inclined at a predetermined angle around a yaw axis with respect to the leg portion.

Images