JP2012089174A - Robot and program of information processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide technology capable of reducing costs required to regenerate an environment map and regenerating the environment map timely.SOLUTION: When map information including the arrangement position of a fixed object within a prescribed area is stored to regenerate a map, (1) to (5) is repeatedly executed while moving a robot 10 within the prescribed area. (1) An encoder 21 is estimated to calculate the self-position of the robot; (2) distances up to a fixed object and a movable object existing within a predetermined viewing angle range of the robot are measured; (3) a corrected self-position is calculated from the measured distances and a distance to the fixed object obtained from map information; (4) a measurement value representing the distance to the movable object within the measurement values is extracted; and (5) the arrangement position of the movable object is calculated from the extracted measurement value and the corrected self-position. Then, the calculated arrangement position of the movable object is subjected to aggregation processing to calculate a new arrangement position, and the calculated new arrangement position is outputted to the outside.

Description

  The present invention relates to a robot program and an information processing apparatus program that can reduce the cost required to re-create an environment map and can re-create the environment map in a timely manner.

  Currently, mobile robots that provide services such as guidance, cleaning, and transportation are used in the service field. This mobile robot moves autonomously according to a predetermined work schedule in order to provide services to humans.

  In the conventional technology, the mobile robot estimates its own position by odometry that calculates the amount of movement by integrating the rotation of the wheels for movement. Odometry is a method of obtaining the translation speed of the robot and the angular velocity of the robot body from the rotational speeds of the left and right wheels, and integrating them to obtain the position and orientation of the robot. Based on the estimated self-position, the mobile robot can move to a required position by traveling along a predetermined route.

  By the way, the environment in which the mobile robot operates is an environment where humans are active. Therefore, the environment usually changes rather than remains unchanged. On the other hand, most mobile robots perform autonomous movement based on a predetermined environmental map. For this reason, when the environment map held by the mobile robot is different from the actual external environment, the self-position recognition function of the mobile robot is degraded.

  In order to prevent the mobile robot's self-position recognition function from being degraded, it is necessary to recreate the environment map to match the environment of the outside world. However, in the re-creation of the environmental map, as in the case of creating a new environmental map, special work by personnel with special skills is indispensable, so improvement in terms of cost and delivery time is required.

  In the technique disclosed in Patent Document 1, when the self-propelled robot learns the movement route, the self-propelled robot set in the learning mode can change the teacher's movement route simply by walking along the movement route. Since automatic processing for determining the route teaching data after the execution is executed, the route can be taught to the self-running robot without the teacher directly editing the position data.

JP 2004-240698 A

However, since the technique described in Patent Document 1 requires on-site teaching, if the instructor with the required skill is separated from the environment in which the mobile robot is operating, the environment changes. Each time it occurs, local teaching is required, leading to an increase in operating costs and a timely response to environmental changes.
In the future, in order to promote the spread of mobile robots in the service field, it is required to reduce the cost required to re-create environmental maps used for mobile robots and to re-create environmental maps in a timely manner.

  The present invention has been made in view of such circumstances, and an object of the present invention is to provide a technology capable of reducing the cost required to re-create an environmental map and re-creating the environmental map in a timely manner. To do.

  The present invention for solving the above-mentioned problems is a program for controlling a robot that automatically moves within a predetermined area, the step of storing map information including an arrangement position of a fixed object within the predetermined area, a map from the outside Steps (1) to (5) are repeatedly executed while the robot is moved within the predetermined area when the re-creation instruction is received. A step of calculating a position, (2) a step of measuring a distance to the fixed object and a movable object within a predetermined viewing angle range of the robot for each specific angle of a horizontal plane, and (3) the measured distance and the map Processing the distance to the fixed object obtained from the information to obtain a corrected self position obtained by correcting the calculated self position; (4) Of the measured values, the movable object (5) calculating the arrangement position of the movable object from the extracted measurement value and the corrected self-position, and aggregating the calculated arrangement position of the movable object Then, a program for causing a computer mounted on the robot to execute a step of obtaining a new arrangement position and a step of outputting the obtained new arrangement position to the outside.

  Further, the present invention is a program for an information processing apparatus, the step of inputting a new arrangement position for the movable object outputted by the robot equipped with the program according to the invention described above, and the new arrangement position. A program for causing a computer mounted on the information processing apparatus to execute a step presented to a user and a step of recreating an environment map in response to a user operation based on the new arrangement position.

  According to the present invention, it is possible to reduce the cost required for re-creating the environment map and to re-create the environment map in a timely manner.

The figure which shows the structure of a map creation system. The figure which shows the structure of a mobile robot. The flowchart which shows operation | movement of the mobile robot at the time of creating a new map. The figure which shows the created map. The flowchart which shows operation | movement of the mobile robot at the time of autonomous movement for work. The flowchart which shows the procedure which correct | amends a self-position. The figure which shows the search method of a corresponding point. The flowchart which shows operation | movement of the mobile robot at the time of recreating a map. The flowchart which shows the general | schematic procedure of a movable object position acquisition process.

[First Embodiment]
FIG. 1 is a diagram showing a configuration of a map creation system.
In this mapping system, the mobile robot 10 provided in the museum 1 and the center information processing terminal 11 of the maintenance center 2 exchange information via the Internet 12 and the wireless LAN router 13. The user information processing terminal 14 provided in the museum 1 can exchange information with the mobile robot 10 and the center information processing terminal 11 via the wireless LAN router 13.

  The mobile robot 10 leads a visitor to the museum 1 and proceeds along a predetermined route, and takes charge of guidance work such as standing in front of each exhibit and explaining the exhibit. In the evening, he is also in charge of patrols such as visiting a predetermined route in the museum.

A maintenance person of the maintenance center 2 can operate the mobile robot 10 remotely by operating the center information processing terminal 11. The mobile robot 10 operates according to a remote command and transmits the collected information to the center information processing terminal 11.
A user of the museum 1 can operate the mobile robot 10 remotely by operating the user information processing terminal 14. The mobile robot 10 operates in accordance with a remote command and transmits the collected information to the user information processing terminal 14.

FIG. 2 is a diagram illustrating a configuration of the mobile robot 10.
The mobile robot 10 includes a general controller 20, an encoder 21, a laser range finder (LRF) 22, a communication unit 23, a remote controller 24, and a data storage device 25.

  The overall controller 20 executes a preset program operation for the mobile robot 10 and controls the operation of the mobile robot 10 in an integrated manner. The encoder 21 is provided on the left and right moving axles of the mobile robot 10 and can measure the rotational speed of the wheels. The self-position of the mobile robot 10 can be estimated from the measured rotational speed by odometry. The LRF 22 is a range sensor, and measures the distance to an object in the visual field range (for example, a range of 240 degrees) of the mobile robot 10 for each specific angle on the horizontal plane. The communication unit 23 exchanges information with the center information processing terminal 11 and the user information processing terminal 14 through a wireless LAN. The remote controller 24 is a control device when the mobile robot 10 is operated by a human operation.

Next, a new map creation operation, an autonomous movement operation, and a map recreation operation of the mobile robot 10 will be described.
FIG. 3 is a flowchart showing the operation of the mobile robot 10 when a new map is created.
In this first map creation, a maintenance person who normally performs work at the maintenance center 2 goes to the site and operates the mobile robot 10 using the remote controller 24, for example.

At the start of operation, the mobile robot 10 sets its own position inside as an initial value. For example, if you are at a standby station, that position is set as the initial self-position.
Next, the mobile robot 10 receives an instruction from the remote controller 24 and executes an operation according to the instruction.

  In step S01, when the received instruction is a rotation / translation movement instruction, the overall controller 20 applies torque to the actuator to move the mobile robot 10 in the instruction direction and stops. At this time, the mobile robot 10 estimates its own position from odometry. Here, the estimated self-position is, for example, an angle θ indicating the X and Y positions and orientations on the plane.

If the received instruction is an outside world data acquisition instruction in step S02, the overall controller 20 causes the LRF 22 to measure and acquire the measured data. In step S03, the measurement data is combined with the environment map stored in the data storage device 25 using the self position as a reference.
FIG. 4 is a diagram showing the created map.
A point group (point cloud) represented by small points in FIG. 4 represents data measured by the LRF 22. As described above, the LRF 22 measures the distance to an object in the visual field range (for example, a range of 240 degrees) of the mobile robot 10 for each specific angle on the horizontal plane. Therefore, the measured value is represented by a plurality of points obtained by measuring the outer shape of the object discontinuously. This is the point group shown in FIG. A map represented by this point cloud is called an environmental map.

  The straight line in FIG. 4 represents the path of the mobile robot. A position represented by a large circle in FIG. 4 represents a position (passing point) where the mobile robot 10 stops to change the moving direction. At this passing point, the mobile robot 10 rotates the specified angle to change the moving direction. A map represented by this route and the stop position is called a route map.

  In step S04 in FIG. 3, the above-described operation is repeated until a map of the movement range is created. In step S05, the created environment map and route map are stored as map information in the data storage device 25 and transmitted to the center information processing terminal 11 via the communication unit 23.

  The transmitted map information, which is the environment map and route map, is stored in the data storage device 32 of the center information processing terminal 11 and further edited by the maintenance person. The maintenance person performs an editing operation via a GUI (Graphical User Interface) while displaying the environment map and the route map using the input / output device 31.

  In step T01, route / point information is edited. For example, a route represented by a straight line in FIG. 4 is added / modified / deleted. In addition, a passing point represented by a large circle in FIG. 4 is added / modified / deleted.

In step T02, a movable / fixed object is set. For example, the attribute of a movable object / fixed object is given to the point group in FIG. Here, the fixed object is an object that exists semi-permanently at a predetermined position, such as a pillar, a specific exhibit, or a fixed wall. A movable thing is a thing other than a fixed thing, for example, what can change an installation position, such as a chair, a specific exhibit, and a simple partition wall.
The maintenance person selects a plurality of point groups (groups) from the point cloud shown in FIG. 4 by dragging and dropping the mouse, and sets group names (names of individual movable objects and fixed objects). Then, set and input the classification information for movable or fixed objects. This operation is repeated to create an environment map file.

  The environment map file is composed of a master file and a slave file.

The master file stores, for each group, coordinates (X, Y), a group name, and a movement type (M, IM) serving as a group reference. The coordinates (X, Y) serving as the group reference are, for example, the coordinates of the point closest to the coordinate origin among the plurality of selected point groups. The movement type represents a classification of a movable object (M: Movable) or a fixed object (IM: Immovable).
A slave file is provided for each group of master files, and coordinates (X, Y) of a plurality of points included in this group are stored.

  In step T03, the work scenario is edited. The maintenance person creates a work scenario that defines the operation of the mobile robot 10. For example, it is defined which route the mobile robot moves from which moving point to which moving point. Further, for example, an operation such as stopping for a predetermined time and outputting a sound for explanation in front of a certain exhibit is defined.

  Each information edited by the maintenance person is transmitted to the mobile robot 10 via the Internet 12 and the wireless LAN 13 and stored in the data storage device 25. The storage status in the data storage device 25 is appropriately transmitted from the mobile robot 10 to the center information processing terminal 11.

FIG. 5 is a flowchart showing the operation of the mobile robot 10 when autonomously moving for work.
The mobile robot 10 starts an operation according to a predetermined work scenario in response to an instruction from the center information processing terminal 11 or an event from a timer.

  In step S11, the mobile robot 10 estimates its own position at the time of activation. Here, when the mobile robot 10 is at a predetermined standby position such as a charging station (not shown), the self-position is immediately determined. However, when not at the predetermined standby position, the self-position is estimated by comparing the point group measured by the LRF 22 with the environment map held in the data storage device 25. When it is difficult to estimate the self position, the measurement is moved to another position and the measurement of the LRF 22 and the self position estimation operation are repeated. The moving direction is a direction in which no object exists in the measurement result of the LRF 22.

  When the self-position can be estimated, an operation state log indicating that the route information and the work scenario are recognized is transmitted to the maintenance center. In step S12, the robot moves to the next point to be moved according to the route information. In step S13, the estimated self-position is calculated from the encoder 21. The encoder 21 calculates the estimated self-position every predetermined distance or every predetermined time during the movement of the robot.

  By the way, the estimated self-position is obtained by integrating the translation component and the rotation component measured using the encoder 21. However, since errors generated when the movement path is not flat and there are irregularities are integrated, it is necessary to appropriately correct the self-position to a correct value.

  Therefore, in step S14, the current estimated self-position by the encoder 21 is corrected based on the environment map and the measurement result of the LRF 22.

FIG. 6 is a flowchart showing a procedure for correcting the self-position.
In step T11, an environment map of the range of the distance measurement range using the LRF 22 is extracted based on the current estimated self-position by odometry. In consideration of the error of the estimated self-position, a portion wide by a predetermined range is extracted.

  In step T12, the points on the environment map and the measurement data of the LRF 22 are subjected to ICP scan matching. That is, separately from the calculation process of the estimated self-position by odometry, the calculation process of the estimated self-position based on the measurement data of the LRF 22 is executed. Here, although there are a movable object and a fixed object on the environment map, the ICP scan matching is performed separately for the movable object and the fixed object.

  Next, an ICP scan matching method will be described.

[A. Nearest neighbor search]
Step A1: The data measured by the LRF 22 is expressed in a robot coordinate system with the mobile robot 10 as a reference (the position of the LRF 22 is the origin). On the other hand, the coordinates of the environment map are expressed in a world coordinate system based on the origin of the environment map. Therefore, the position of the measured point is converted from the robot coordinate system to the world coordinate system (homogeneous conversion). The coordinates of the measurement point (conversion point) after the homogeneous conversion are expressed by equation (1).

  Here, the first term on the right side of the equation (1) is a rotation component for correcting the orientation of the mobile robot 10, and the second term represents the translation component of the mobile robot 10.

Step A2: The conversion point obtained by the equation (1) and the point (reference point) on the environment map where the distance is the minimum are searched, and a set of these two points is set as a corresponding set.
FIG. 7 is a diagram illustrating a method for searching for a correspondence group. When there are i conversion points qt and j reference points p, the distances from all the reference points are obtained for each conversion point. Then, for each conversion point, a reference point having a minimum distance is selected, and the conversion point and the reference point are associated with each other to obtain a corresponding set. During this search, outlier removal is always performed. In the outlier removal, when the distance calculated during the search is equal to or larger than a predetermined threshold, it is excluded from the selection target and also excluded from the subsequent processing targets.

  Note that outlier removal is not limited to the above-described search. If the distance between the conversion point and the reference point of the corresponding pair obtained as a result of this search is equal to or greater than a predetermined threshold, the target of subsequent processing You may make it exclude from.

[B. Update outlier removal parameter]
The threshold for removing outliers is obtained by multiplying the average value of the distance between the conversion point of each corresponding set obtained in the previous search and the reference point by a predetermined multiple (for example, twice) of the standard deviation. The value obtained by the sum of is used. Therefore, the threshold value for outlier removal obtained in the current search is used in the next search.

[C. Update homogeneous transformation values using Newton's method]
Here, the initial self-position and the update self-position are updated so that the conversion point qti (n) obtained from the equation (1) approaches the corresponding reference point pj. At this time, the internal data of the self position is updated, and the self position is not updated by actually moving the robot.

Therefore, Step C1: An evaluation function is introduced that serves as an index as to whether or not the conversion point qti (n) and the reference point pj are close to each other. Next, by using Newton's method which is one of optimization methods for the evaluation function in Step C2: Step 1, processing is performed so that the conversion point qti (n) approaches the corresponding reference point pj. Step C3: Corresponding to this processing, the robot's initial self-position and update self-position (tx (n), ty (n), tθ (n)) are updated (tx (n + 1), ty (n + 1), tθ (n + 1)). Step C4: The squares of the differences between the corresponding components of the self-position after update and the self-position before update are respectively obtained, and the sum of these values is calculated. Step C5: A new conversion point is calculated based on the updated self-position, and the processes from Step C2 to Step C4 are repeated using the new conversion point until the total value becomes equal to or less than the threshold value. When the total value is equal to or less than the threshold value, the ICP scan matching is finished. The updated self-position at this time is the result of ICP scan matching, that is, the estimated self-position by the LRF 22.

  In the process from step C2 to step C5, it is assumed that the distance between the conversion point and the reference point in step C2 is equal to or less than a threshold value. Even if the total value is equal to or less than the threshold value, the conversion point in step C2 is determined. If the number of repetitions of the processing from step C2 to step C4 exceeds the threshold without the distance between the reference point and the reference point being equal to or less than the threshold, an error may be output and the processing may be terminated. The errors output at this time can be aggregated and used as an index indicating whether or not map re-creation is necessary as a matching error rate. For example, when the robot executes steps C1 to C5 at n points in the travel space and m points are output as matching errors, the matching error rate is (m / n). It is calculated as x100, and when this value exceeds the threshold value, it is determined that map recreation is necessary.

  After calculating the estimated self-position by the LRF 22 by ICP scan matching as described above, the current estimated self-position by the encoder 21 is corrected in step T13 of FIG.

  For this purpose, the estimated self-position by the LRF 22 based on the movable object, the estimated self-position by the LRF 22 based on the fixed object, and the estimated self-position by the encoder 21 are fused by the maximum likelihood estimation method using the Kalman filter. To calculate a new self-position. The new self-position calculated here is the self-position after correction. This fusion process takes into account the magnitude of the estimated self-position error by the encoder 21 and the magnitude of the estimated self-position error by the LRF 22, and weights depending on the magnitude of these errors to provide a more accurate result. Includes the process of calculating the self-position. The fusion by the maximum likelihood estimation method using the Kalman filter can be performed with reference to, for example, Journal of the Robotics Society of Japan Vol.22 No.3, pp.343-352, 2004.

  Note that the new self-position is estimated from the two self-positions obtained from the movable object and the fixed object by fusion because, for example, when measuring a wide and simple space, the fixed object is small. This is because, in the case where the error of the self-position based on the case becomes large, the deterioration of accuracy is prevented by incorporating the self-position information by the movable object.

  Therefore, as shown in the present embodiment, when the target area is limited and the number of fixed objects necessary for self-position calculation is arranged, it is not necessary to perform the fusion process on the movable objects.

  As a method of fusing the two estimated self-positions obtained from the movable object and the fixed object when the fixed object is sparse in the traveling space, for example, the measurement result of the LRF 22 for the distance from the current self-position to the fixed object. And corresponding points on the environment map are compared with each other to calculate an error rate. If this error rate is equal to or less than a threshold value, the fusion ratio of movable objects is set to zero. When the threshold value is exceeded, the fusion ratio of the movable object is set by a coefficient depending on the error rate, and the two estimated self-positions obtained from the movable object and the fixed object are fused according to the fusion ratio.

  The mobile robot 10 collates the self-position calculated by the above procedure with the environment map. Then, in step S15 of FIG. 5, it is determined whether or not the destination has been reached.

If No in step S15, that is, if the destination has not yet been reached, the mobile robot 10 continues the operation from step S12 described above. In this way, the mobile robot 10 repeatedly executes the correction of the current estimated self-position by the encoder 21 every predetermined distance or every predetermined time even during movement.
If Yes in step S15, that is, if the destination is reached, in step S16, if there is a work registered in the work scenario at that point, the work is executed.

  In step S17, when a need arises during the robot operation, an operation state log is transmitted to the maintenance center as needed. This operation state log includes the current location, the contents of work performed, the matching error rate between the outside world and the environment map, and the like. Then, the mobile robot 10 continues the operation from step S12 described above toward the next destination.

  In the maintenance center, it is determined whether or not the mobile robot 10 is operating normally based on the operation log. For example, in the measurement by the LRF 22 for a movable object, if the ratio of measurement points having an error more than a predetermined value with the environment map, that is, the matching error rate increases and exceeds the threshold value, the mobile robot 10 is broken. Or the necessity of map re-creation is considered. Further, when the difference between the estimated self-position based on odometry and the estimated self-position based on LRF 22 continuously exceeds a threshold value, it may be determined that map re-creation is necessary.

For example, regarding the distance to an object (a fixed object and a movable object), if the index value indicating the degree of error between the measured value and the distance obtained from the map information is increasing, the accuracy of the mobile robot 10 is poor. Therefore, it can be judged that an accuracy inspection is necessary.
In addition, the index value indicating the degree of error between the measured value and the distance obtained from the map information is increased with respect to the distance to the movable object, and the distance between the measured value and the map information is obtained with respect to the distance to the fixed object. If the index value indicating the degree of error has not increased, it can be determined that map re-creation is necessary because of the movement, appearance, and disappearance of movable objects.

  If the mobile robot 10 detects that the remaining battery level is equal to or lower than the threshold, the mobile robot 10 switches the work scenario to return to the charging station and moves to the charging station according to a predetermined route.

FIG. 8 is a flowchart showing the operation of the mobile robot 10 when recreating a map.
For example, when the index value indicating the degree of error between the measured value and the distance obtained from the map information is equal to or greater than a predetermined value, the map is recreated based on the judgment of the maintenance person of the maintenance center 2. The processing is started by a map re-creation instruction transmitted from the information processing terminal 11.

  Specifically, if the actual environment changes and differs from the environment when the environment map was created in advance, instructions from the maintenance staff (via the Internet) at night or on closed days after the environment change. The map can be autonomously recreated by a trigger such as a predetermined schedule (for example, a predetermined period of time).

  In step S21, the closed area is searched based on the environment map in which the fixed object and the movable object are described. As a search method, a known technique such as a New Frontier method can be used. In step S22, the overall controller 20 causes the LRF 22 to measure and obtain the measured data. In step S23, a movable object position acquisition process (FIG. 9) is executed. The purpose of step S23 is to obtain an accurate position of the movable object based on the corrected self position after correcting the self position based on the position of the fixed object.

FIG. 9 is a flowchart showing a schematic procedure of the movable object position acquisition process.
In step T21, the point group measured by the LRF 22 is subjected to homogeneous transformation. In step T22, the measurement value subjected to the homogeneous conversion is compared with a point group representing a fixed object described in the environment map. In step T23, ICP scan matching is performed to correct the self position. The processes in steps T22 and T23 are the same as the processes in steps T12 and T13 in FIG. If there is no measurement point corresponding to the fixed object, the self-position obtained from the measurement value by the encoder 21 is maintained.

  In step T24, a point group other than a fixed object is set as a movable object. For example, a predetermined area centering on the coordinate point of each fixed object represented in the world coordinate system on the environment map is set, and a point group outside the area is set as a movable object. Then, the position of the movable object is obtained in the world coordinate system based on the corrected self-position.

  In step T25, the obtained position of the movable object is temporarily stored. Then, the process returns to FIG.

In step S24 of FIG. 8, the above-described steps S21 to S23 are executed until the closed region is searched throughout. When the search is finished, the coordinate positions of the movable objects are collected in step S25.
Aggregation is a process performed to prevent a reduction in processing efficiency due to the location of a large number of movable objects in the search described above.

  Therefore, in step S25, the obtained measurement points of the movable object are collected. For example, as a method of aggregation, measurement points for movable objects are selected by thinning. For example, measurement points extracted every n (an integer of 2 or more) are selected as measurement points for a new movable object, and set as measurement points for a new movable object. In addition, as a method for obtaining a measurement point for a new movable object, a representative point is selected from neighboring measurement points, and this may be used as a measurement point for a new movable object, or a measurement point for a movable object. The points corresponding to the average value of the positions of the plurality of measurement points belonging to the group may be newly set as the measurement points of the movable object. Also, moveable objects are grouped into multiple groups, for example by factor analysis and using Mahalanobis distance. Then, the average value of the positions of a plurality of points belonging to the group may be newly aggregated as the position of the movable object. Furthermore, the above-described methods may be combined in an appropriate order to obtain a new movable object measurement point.

  Here, if it is within a predetermined area centered on the coordinate point of each fixed object represented in the world coordinate system on the environment map, it is a fixed object, and if it is outside the area, it is a movable object. A plurality of points existing within a certain range after combining them on the map are merged to improve processing efficiency and treated as one point in the subsequent processing.

In step S26, the collected position data of the movable object is stored in the data storage device 25 and transmitted to the center information processing terminal 11 via the communication unit 23 in step S27.
The transmitted location data of the movable object is stored in the data storage device 32 of the center information processing terminal 11. The center information processing terminal 11 further creates an environmental map based on the position data and presents it to the maintenance person. The maintenance person further edits the presented environmental map to recreate a desired environmental map.

  Note that the aggregated movable object position data is transmitted to the center information processing terminal 11 in order to reduce the transmission amount, but of course, an environment map including the aggregated movable object position data is used as the center information processing terminal. 11 may be transmitted.

[Effect of the embodiment]
According to the embodiment described above, the following effects can be obtained in map re-creation.

  The mobile robot 10 moves while automatically correcting its own position, and further automatically recreates a map. Accordingly, it is possible to constantly create a high-precision map and reduce the user's economic and time burden.

  Furthermore, the mobile robot 10 corrects its own position based on a fixed object on the environment map, specifies a movable object based on the corrected self position, and calculates its position. Then, the position of the movable object is aggregated to obtain a new position of the movable object. As a result, the position accuracy of the movable object is improved and a highly accurate map can be efficiently created.

  Furthermore, the mobile robot 10 performs the calculation of the estimated self-position by the LRF separately for the movable object and the fixed object based on the environment map. Then, the error of each sensor can be canceled by fusing the estimated self-position by the LRF based on the movable object, the estimated self-position by the LRF based on the fixed object, and the estimated self-position by the encoder. . As a result, accurate self-position correction can be performed.

  In addition, the mobile robot calculates an index value representing the degree of error between the LRF measurement value and the distance obtained from the map information during work, and transmits it to the maintenance center. Therefore, the maintenance center can grasp the necessity of the accuracy inspection of the mobile robot and the necessity of re-creating the map without going to the site by managing the index value.

  Each function described in the above embodiment may be configured using hardware, or may be realized by reading a program describing each function into a computer using software. Each function may be configured by appropriately selecting either software or hardware.

  Furthermore, each function can be realized by causing a computer to read a program stored in a recording medium (not shown). Here, as long as the recording medium in the present embodiment can record a program and can be read by a computer, the recording format may be any form.

Note that the present invention is not limited to the above-described embodiment as it is, and can be embodied by modifying the constituent elements without departing from the scope of the invention in the implementation stage.
Further, various inventions can be formed by appropriately combining a plurality of constituent elements disclosed in the embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, you may combine suitably the component covering different embodiment.

    DESCRIPTION OF SYMBOLS 1 ... Museum, 2 ... Maintenance center, 10 ... Mobile robot, 11 ... Center information processing terminal, 12 ... Internet, 13 ... Wireless LAN router, 14 ... User information processing terminal, 20 ... General controller, 21 ... Encoder, 22 ... Laser Range finder, 23 ... communication unit, 24 ... remote controller, 25 ... data storage device, 31 ... input / output device, 32 ... data storage device.

The present invention reduces the cost of re-creating the environmental map, and a program for the robot及 beauty information processing apparatus capable of re-creating an environmental map in a timely manner.

The present invention for solving the above problems is a robot and a control method for an information processing apparatus in a system including a robot that automatically moves within a predetermined area and an information processing apparatus connected to the robot via a communication line. The robot searches the predetermined area based on map information including position information of the fixed object and the movable object in the predetermined area according to a command from the information processing apparatus or a predetermined schedule. Collecting the position information of the movable object based on the measured position of the fixed object, and transmitting the collected position information of the movable object to the information processing apparatus, In accordance with the step of updating and presenting map information based on the position information of the movable object transmitted by the robot, and according to the input operation instruction Editing a work scenario that defines a moving route and an operation and new map information; and transmitting the edited map information and the work scenario to the robot. And automatically moving in the predetermined area according to the map information and the work scenario.

Further, the present invention is a program for controlling a robot and an information processing apparatus in a system including a robot that automatically moves within a predetermined area and an information processing apparatus connected to the robot via a communication line. In the installed computer, in accordance with a command from the information processing apparatus or a predetermined schedule, the inside of the predetermined area is searched based on map information including position information of the fixed object and the movable object in the predetermined area. Mounting the position information of the movable object on the basis of the measured position of the fixed object and the step of transmitting the collected position information of the movable object to the information processing apparatus. Updating and presenting the map information to the computer based on the position information of the movable object transmitted by the robot; Editing a work scenario that defines the path and movement of the robot and new map information in accordance with an input operation instruction; and transmitting the edited map information and the work scenario to the robot. And the computer mounted on the robot is caused to execute a step of automatically moving in the predetermined area according to the transmitted map information and the work scenario.

Claims (5)

A program for controlling a robot that automatically moves within a predetermined area,
Storing map information including an arrangement position of a fixed object in the predetermined area;
A step of repeatedly executing the steps (1) to (5) while moving the robot in the predetermined area when receiving an instruction to re-create the map from the outside;
(1) a step of calculating the self-position of the robot by integrating the measured values of the encoder;
(2) measuring a distance to the fixed object and the movable object within a predetermined viewing angle range of the robot for each specific angle of a horizontal plane;
(3) processing the measured distance and the distance to the fixed object obtained from the map information to obtain a corrected self-position obtained by correcting the calculated self-position;
(4) extracting a measurement value representing a distance to the movable object among the measurement values;
(5) calculating an arrangement position of the movable object from the extracted measurement value and the corrected self-position;
A step of aggregating the calculated arrangement position of the movable object to obtain a new arrangement position;
Outputting the determined new arrangement position to the outside;
For causing a computer mounted on the robot to execute the program. The program according to claim 1,
The map information further includes an arrangement position of the movable object within the predetermined area,
Calculating each index representing the degree of error between the measured distance and the distance to the fixed object and the movable object obtained from the map information;
Outputting each calculated index to the outside,
For causing the computer mounted on the robot to further execute the above.   The program according to claim 1, wherein in the aggregation process, a thinning process is performed on the calculated arrangement position of the movable object. An information processing apparatus program,
A step of inputting a new arrangement position of the movable object output by the robot loaded with the program according to claim 1;
Presenting the new location to the user;
Re-creating a map in response to a user operation based on this new location,
For causing a computer mounted on the information processing apparatus to execute the program. An information processing apparatus program,
A step of inputting an index representing a degree of error for each of the fixed object and the movable object output by the robot loaded with the program according to claim 2;
Presenting to the user an index representing the degree of the error;
Outputting a map re-creation instruction to the robot in response to a user operation based on the index;
For causing a computer mounted on the information processing apparatus to execute the program.

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