JP2008009928A - Mobile robot - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To surely detect the wetting of a road surface in rain, and to use it as control information for securing precision in judging an obstacle in a mobile robot, and the like. <P>SOLUTION: A laser sensor 2 of a mobile robot carries out scanning with a laser beam to a road surface in a prescribed cycle, and outputs a detection signal after receiving reflected rays of light. A control part 21 recognizes that the detection signals whose distance values are a fixed value or less among N pieces of detection signals acquired in one cycle are from a dry road surface, and judges that the road surface is dry when the rate of the number of count of the detection signals whose distance values are the fixed value or less to the whole number of the detection signals is a prescribed value or more, or judges that the road surface is wet otherwise. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a mobile robot that travels outdoors while detecting an obstacle on a traveling road surface, and more particularly to a technique for ensuring the accuracy of detecting an obstacle even when the traveling road surface is wet.

  2. Description of the Related Art Conventionally, a mobile robot that travels while detecting an obstacle on a traveling road surface uses a distance detection sensor to emit laser light for distance measurement in the left-right direction toward the floor (traveling road surface) as disclosed in Patent Document 1. Light was projected and received at predetermined sampling intervals, and obstacles were detected based on the obtained distance data.

  FIG. 10 is a diagram for explaining a state of obstacle detection by the conventional mobile robot R, and shows a side view of the positional relationship among the mobile robot R, laser light L, traveling road surface S, and obstacle H on the right side. The left side shows a plan view of the distance data measured by the distance detection sensor. The distance data on the left is schematically shown in an orthogonal coordinate system viewed from the left and right (X axis direction) and front and rear (Y axis direction) with the distance detection sensor as the center. Further, in order to see the movement history of the mobile robot R, the mobile robot R is shown in a line up and down in order of time t, t + 1, t + 2, t + 3, and t + 4.

  At time t, the laser beam L of the mobile robot R is projected onto the traveling road surface S, and the reflected light from the traveling road surface S is received. For this reason, as shown in the left column, the distance to the place where the laser light L of the traveling road surface S hits is measured.

At time t + 1, the mobile robot R is slightly closer to the obstacle H, and the laser beam L is in a state where it hits a height close to the traveling road surface S of the obstacle H. In this case, as shown in the left column, the measured distance data has a difference between the distance from the reflected light from the traveling road surface S and the distance from the reflected light from the obstacle H.
At t + 2, the mobile robot R is closer to the time point t + 1, and the laser beam L has hit an intermediate height of the obstacle H. In this case, as shown in the left column, the measured distance data has a difference between the distance due to the reflected light from the traveling road surface S and the distance due to the reflected light from the obstacle H greater than the time point t + 1.
At t + 3, the mobile robot R is closer to the time point t + 2 and the laser beam L hits the upper part of the obstacle H. In this case, as shown in the left column, in the measured distance data, the difference between the distance from the reflected light from the traveling road surface S and the distance from the reflected light from the obstacle H becomes larger than the time point t + 2.

At t + 4, the laser beam L of the mobile robot R passes over the obstacle H and is projected onto the traveling road surface S, and the reflected light from the traveling road surface S is received. For this reason, as shown in the left column, the distance to the place where the laser light L of the traveling road surface S hits is measured.
Normally, in order to prevent the mobile robot R from colliding with the obstacle, a stop or avoidance operation is performed when the obstacle H is detected, so that control is performed so as not to move to t + 4. It is described for the purpose.

In the mobile robot R, the obstacle H is detected based on the distance data as shown in the left column of FIG. That is, as is apparent from the figure, the distance data based on the reflected light from the traveling road surface S is measured as substantially equidistant data, and the obstacle H is closer to the distance data than the distance data based on the reflected light from the traveling road surface S. It becomes data. Therefore, in the mobile robot R, if there is a distance difference of a predetermined threshold or more from the distance data by the traveling road surface S, it is detected as an obstacle. Note that the predetermined threshold value is used to determine whether or not the obstacle is an obstacle in consideration of the fact that the distance difference corresponds to the height of the obstacle from the road surface.
Japanese Unexamined Patent Publication No. 1-293410

  However, when it rains and the road surface gets wet, it is difficult to obtain a correct distance value by the laser sensor. In particular, when the laser sensor is installed at a shallow angle with respect to the road surface, depending on the road surface condition, the laser beam is specularly reflected and the distance value cannot be obtained at all, or the waveform of the signal from the received reflected light The error of the distance value may become large because it is difficult to determine the rising position. If the distance value error results in a shorter value (closer distance) than the actual road surface, it may be mistaken for an obstacle. May be judged.

  For example, if the robot travels at a speed of 10 km / h (277.7 cm / s) and the sampling period of the laser sensor is 33 ms, sensor data is obtained every time the robot moves 9.2 cm. Here, when laser light hits the obstacle, if the sensor mounting angle is about 10 degrees, the position where the laser light hits the obstacle is 1.6 cm (= tan10 ° in the height direction of the obstacle as the robot moves) * 9.2) It will be shifted one by one.

Here, when the robot can get over a step of up to 5 cm, it is necessary to detect an object having a height of 5 cm or more as an obstacle that hinders running.
Therefore, in order to find an obstacle 5 cm high, the sensing result must be within the range of 3.4 cm <h ≤ 5 cm, that is, the threshold must be set as 3.4 cm to reliably find a 5 cm object. .

  However, as described above, the error increases when the road surface gets wet, and if a value shorter than the actual distance is obtained, an object with a height of 3.4 cm or more is erroneously detected even if the object is low in height. There was a problem that there is a possibility.

  Thus, when the road surface is wet, there is a possibility that the accuracy of the obstacle determination may be lowered in the normal obstacle determination method as described above, and a more appropriate obstacle determination method by detecting the wetness of the road surface. It is more preferable if it can be switched to.

  However, in the past, a method for reliably determining whether or not the road surface is wet has not been established. Control of mobile robots, such as switching control methods such as obstacle detection according to road surface conditions such as wetness, etc. However, it is difficult to effectively use the wetness of the road surface as control information.

  The present invention has been made in view of the above problems, and detects the wetness of the road surface due to rain or the like in the control of the mobile robot, and maintains the road surface wetness information, for example, the detection accuracy of obstacles that can be changed by the wetness of the road surface. Therefore, it is intended to be used as control information in general control of a mobile robot, such as use as road surface information at the time of obstacle determination.

The mobile robot of the present invention described in claim 1 is:
A mobile robot that detects the wet state of a traveling road surface,
A distance measuring sensor that transmits a detection wave for distance measurement to the road surface and receives a reflected wave to measure a distance to the mobile robot;
Obstacle determination means for detecting an obstacle on the road surface based on distance data measured by the distance measuring sensor;
Road surface condition determining means for detecting a wet state of the road surface based on distance data outside a predetermined range measured by the distance measuring sensor or unmeasurable distance data;
It is characterized by comprising.

The mobile robot of the present invention described in claim 2 is the mobile robot according to claim 1,
The distance measuring sensor transmits a predetermined number of detection waves to the road surface and receives reflected waves,
The road surface condition judging means is wet if the ratio of the number of distance data outside the predetermined range or the distance data that cannot be measured to the total or part of the detected wave numbers transmitted is equal to or greater than a predetermined threshold. It is characterized by judging.

The mobile robot according to claim 3 is the mobile robot according to claim 1 or 2,
The obstacle determining means is characterized in that logic for detecting an obstacle is made different according to the determination by the road surface condition determining means.

The mobile robot according to claim 4 is the mobile robot according to claim 2 or 3,
The predetermined number of detection waves in the distance measuring sensor is a number necessary for scanning a predetermined area of the road surface including at least the front in the traveling direction.

  Further, according to the present invention, in the processing of a plurality of reflected waves obtained by the distance measuring sensor, for example, the ratio of the total number of distance data within a predetermined range to all or a part of the detected wave numbers transmitted is equal to or greater than a predetermined threshold. In some cases, the road surface may be determined to be dry (not wet), and the road surface may be determined to be wet if the ratio is less than a predetermined threshold.

According to the mobile robot described in claim 1, using a distance measuring sensor provided in advance for obstacle detection, the presence / absence of an obstacle is determined from the measurement result, and whether the road surface is wet is also determined. It is possible to provide a wet road surface discrimination function while reducing the cost burden without providing a separate detection means for detecting the wet road surface.
According to the mobile robot described in claim 2, by transmitting a detection wave toward a different position, the reflected wave is obtained, and a reflected wave is obtained from a plurality of target detection waves. It is determined whether or not the road surface is wet based on the ratio indicating the distance that does not exist or exceeds the predetermined range, so that it is possible to reliably determine whether the road surface is wet. This information about road wetting should be widely used as control information in general control of mobile robots, for example, it can be used as road surface information when judging obstacles to maintain the accuracy of detecting obstacles that can change due to road wetting. Can do.

  According to the mobile robot described in claim 4, the determination as to whether or not the road surface is wet is made based on one cycle of scanning by the distance measuring sensor, so that the determination can be made quickly and reliably.

1. Overall configuration (Figure 1)
FIG. 1 is a plan view of a monitoring area, which is an environment in which a mobile robot 1 according to an embodiment of the present invention is used, and a perspective view showing an appearance of the mobile robot 1.
The mobile robot 1 is an autonomous mobile robot used for security purposes, for example, and uses an abnormality determination sensor, an imaging unit 7 and a laser sensor 2 (not shown) while traveling around a predetermined route in the monitoring area. To detect abnormalities in the monitoring area.

  In FIG. 1A, the periphery of the building is a moving route that the mobile robot 1 circulates in advance, and a white line tape 3 as a guide means is fixedly provided over the entire length of the moving route. . The monitoring area is a range of a predetermined area including the building and the white line tape 3 set to go around the building.

  In addition, at a predetermined point in the route, an indication marker 4 as a point indication means is fixedly arranged in the vicinity of the white line tape 3. The instruction marker 4 is provided as a white rectangular mark at the boundary of the travel section set on the travel route, and the travel section set on the travel route and the point where the instruction marker 4 is set are indicated to the mobile robot 1. It is an instruction.

  In the middle of the white line tape 3, there are a starting point (starting point) and an ending point (arrival point) in one cycle of the monitoring patrol action by the mobile robot 1, which is a hangar when the robot is not used, and further the mobile robot 1 A robot box having a charging device for charging the battery is arranged.

  Although not shown in FIG. 1, for example, a monitoring center is installed in a security-related department in the building. In this monitoring center, the mobile robot 1 of this example and a control device for operating the system related thereto are arranged, and a staff member is in charge of the operation.

  As shown in FIG. 1 (b), the mobile robot 1 is an obstacle detection means equipped on the front side of the main body while traveling along the white line tape 3 with the left and right wheels 6 as the movement means. The laser sensor 2 scans the monitoring area ahead of the moving direction as shown by the dashed line in the figure. The upper part of the main body is equipped with an imaging unit 7 that can image the entire periphery, and when an abnormality is found by the laser sensor 2 or the like or when necessary, an image of a necessary position in the periphery can be captured. Yes.

  When the mobile robot 1 detects an abnormality in the monitoring area during the monitoring patrol action, the mobile robot 1 sends an abnormal signal together with the captured image to the remote monitoring center. When the monitoring center receives the abnormality signal, the received captured image is displayed to check the abnormality, and the mobile robot 1 is remotely operated to deal with the abnormality.

2. Configuration of mobile robot 1 (FIGS. 1 and 2)
FIG. 2 is a functional block diagram showing a specific configuration of the mobile robot 1 of this example.
This mobile robot 1 includes moving means 6 and 8, a guide detection unit 10, a movement control unit 9, a self-position detection unit 13, a distance measuring sensor 16, a storage unit 17, a processing unit 18, an imaging unit 7, a communication unit 20, and these It has the control part 21 which controls each part, and the power supply part 22 which supplies electric power to each part. Each part will be described below.

(1) Moving means The mobile robot 1 has four wheels 6 as shown in FIG. 1B, and two of them, the right front wheel 6 and the left front wheel 6, function as drive wheels. The moving means is composed of two motors 8 for independently driving the right front wheel 6, the left front wheel 6 and the left and right front wheels 6, and the straight traveling speed and the turning traveling speed are controlled by the rotational speed of the left and right front wheels 6, The turning direction is also controlled. The rotational speed of the left and right front wheels 6 is controlled by the movement control unit 9. Instead of controlling the left and right front wheels 6 independently, a method of controlling the turning speed by controlling the steering angle may be used, or a method of independently controlling the left and right crawlers instead of driving the wheels.

(2) Guide Detection Unit The guide detection unit 10 detects the above-described white line tape 3 which is guide means on the moving path.
The guide detection unit 10 includes a white line detection camera 11 and a road surface information extraction unit 12. The white line detection camera 11 is installed on the bottom surface of the mobile robot 1 so that the road surface can be photographed. The road surface information extraction unit 12 detects the white line tape 3 and the pointing marker 4 that should guide the route of the mobile robot 1 from the photographed image of the white line detection camera 11 by processing such as edge extraction and Hough conversion, and sends it to the control unit 21. Output.

  Note that the guide detection unit 10 may be configured by a magnetic sensor, an electromagnetic induction sensor, or the like, and may detect a magnetic guide or an electromagnetic induction guide as guide means installed in the moving path. It is preferable that the guide means and the guide detection unit can be selected depending on the installation environment. Further, each point on the patrol route may be recognized based on position information calculated by dead reckoning or GPS without providing a guide unit or a point instruction unit on the patrol route.

(3) Movement control part The movement control part 9 is a means for controlling the motor 8 which drives the wheel 6 of a moving means. The movement control unit 9 controls the motor 8 so that the mobile robot 1 moves along the white line tape 3 by, for example, well-known PID control according to the detection output of the white line tape 3 by the guide detection unit 10. Further, the movement control unit 9 controls the movement speed based on preset route information according to the detection of the travel section by the position calculation unit 15 of the self-position detection unit 13 described later, and the specific point by the position calculation unit 15 Stops traveling in response to detection of.

(4) Self-position detection unit The self-position detection unit 13 includes a resolver 14 as a rotation amount detection unit installed in each motor 8 of the moving means, and a position calculation unit 15 connected to each resolver 14. . The resolver 14 detects the absolute position of the rotating shaft of the motor 8. The position calculation unit 15 calculates the rotation amount of each of the left and right front wheels 6 from the rotation amount of the rotation shaft of the motor 8 obtained from the output of the resolver 14, and calculates the left and right calculated from the rotation amount and wheel radius of each of the left and right front wheels 6. The travel distance of the mobile robot 1 is calculated from the average travel distance of each front wheel 6.

  In this example, since the traveling route of the mobile robot 1 is fixed, the traveling distance can be set as the self-position. The travel distance may be recorded as the total distance from the start point or as the distance from the position of each indication marker 4. The position calculation unit 15 calculates the change in the posture (orientation) of the mobile robot from the difference in rotation amount between the left and right front wheels and the wheel interval, and calculates the self position by dead reckoning from the travel distance and posture change by the left and right front wheels. May be.

  The self-position calculating unit 13 counts the number of detections of the indication marker 4 according to the detection output of the indication marker 4 by the guide detection unit 10, detects the current travel section based on the route information, and Make corrections.

(5) Ranging Sensor The ranging sensor 16 is a means for scanning the front of the mobile robot 1 to measure the state of the road surface and the distance to foreign objects on the road surface and other detection targets.
As shown in FIG. 3, the distance measuring sensor 16 includes a laser sensor 2 installed on the front side of the main body of the mobile robot 1 so as to face forward and downward in the traveling direction. The laser sensor 2 includes a projecting / receiving wave unit that irradiates a laser beam as a detection wave from a laser oscillator and outputs a detection signal by receiving reflected light when reflected by an object on the optical path of the laser beam. Yes. The laser sensor 2 has a scanning mirror that is a scanning means for laser light and means for rotationally driving the scanning mirror, and the irradiation direction (irradiation angle) of the laser light emitted from the laser oscillator is determined on the road surface. A predetermined range including the front of the mobile robot 1 is spatially scanned at a predetermined cycle (for example, 33 ms) by controlling to face a plurality of different positions.

  3A shows the geometric positional relationship between the laser sensor 2 and the measurement point in the mobile robot 1 of this example, and FIG. 3B shows the scanning angle range Φ of the laser sensor 2. An example of the sensing area (hatched area) indicated by and the number of sensor measurement data in the area is shown. As shown in the figure, in this example, 140 ° in front of the mobile robot 1 is set as a sensing area by the laser sensor 2, and the scanning mirror is rotated by 0.5 ° to scan the sensing area. As a result, data of 281 measurement points are obtained in one cycle of scanning by the laser sensor 2.

  Then, the distance measuring sensor 16 calculates the distance between the distance measuring sensor 16 calculated by the time from the irradiation of the laser light to the detection of the reflected light and the object (measurement point) reflecting the laser light, and the scanning mirror driven to rotate. Based on the angle, the relative position of the object reflecting the laser beam, that is, the measurement point reflecting the laser beam is calculated. The relative position is the position (distance value, angle) of the measurement point with reference to the mobile robot 1. The distance measuring sensor 16 outputs a measurement result every time the laser sensor 2 scans for one period.

  The distance measuring sensor 16 may be composed of a sensor other than the laser sensor. For example, the distance measuring sensor 16 may be constituted by an infrared type sensor, or may be constituted by a millimeter wave radar type sensor or an ultrasonic sensor. In addition to a configuration that scans with a scanning mirror, a plurality of light projecting / receiving units are provided for each predetermined angle around the mobile robot, and by operating each of the light projecting / receiving units at a predetermined cycle, the road surface and obstacles below the surroundings The distance value may be obtained. In this case, the distance measuring sensor 16 collectively outputs the measurement results of the light projecting and receiving units.

(6) Storage Unit The storage unit 17 stores information used for various processes of the mobile robot 1. The information stored in the storage unit 17 includes the following items 1) to 4).
1) Route information showing travel route information
2) Obstacle map
3) Position information of the mobile robot 1 calculated by the position calculation unit
4) Threshold for obstacle judgment

  The route information of 1) corresponds to the number of each section (section from one indication marker 4 to the next indication marker 4) in the traveling route, and the traveling speeds maxH and maxL (maxH> maxL) within the section, The section distance measured, the difference in azimuth between the start point and end point of the section (angle difference), the wheel diameter when traveling in each section, and the operation of the mobile robot 1 on each indication marker 4 are stored. In the route information, the section number is associated with the number of indication markers 4 (number of detections) to be detected by the corresponding section. In the traveling control, the section number and the operation of the mobile robot 1 on the instruction marker 4 are specified from the number of detections of the instruction marker 4, and the wheel diameter in each section is specified from the section number.

  The obstacle map 2) is a map showing a predetermined range around the mobile robot 1 for temporarily storing obstacle information detected by the distance measuring sensor 16 and the processing unit 18. As shown in FIG. 4, a stop area and a deceleration area are set and detected in the map area with the position of the laser sensor 2 installed in the mobile robot 1 as the origin (0, 0). Obstacles and road wetting information are registered on the map. Each time the mobile robot 1 travels, coordinate conversion of obstacle data registered on the map is performed in accordance with the movement.

The position information 3) is self-position information of the mobile robot 1 calculated by the position calculation unit 15 of the self-position detection unit 13.
The threshold for obstacle determination in 4) is a threshold that is compared with a value corresponding to the height of the object in order to detect an object having a height that interferes with traveling that the mobile robot 1 cannot get over as an obstacle. It is. As a value set as a threshold, a relatively large value thH (a strict value as a threshold for determining that there is an obstacle) and a relatively low value thL (a loose value as a threshold for determining that there is an obstacle) Two values are stored in advance, and any one of them is set as an obstacle determination threshold value in the control related to obstacle detection described later.

(7) Processing Unit The processing unit 18 includes a road surface state determination unit 23 and an obstacle determination unit 19. The road surface state determination unit 23 determines whether the road surface state is dry or wet based on the output result of the laser sensor 2, and outputs the determination result to the control unit 21. As a result, the control unit 21 outputs a signal to the movement control unit 9 so as to travel at the upper limit speed (maxH or maxL) according to the road surface condition. The obstacle determination unit 19 determines whether there is an obstacle abnormality on the obstacle map based on the output of the distance measuring sensor 16. The obstacle determination unit 19 compares the distance value included in the data output as the scanning result of one cycle of the distance measuring sensor 16 with a threshold (thH or thL), and has an obstacle having a height higher than a predetermined value. It is determined whether or not exists. As described above, the distance value difference (the distance value difference for each angle of the scanning mirror) included in the data output as a result of the distance measurement sensor 16 scanning the road surface is a value corresponding to the height of the obstacle. Become. By performing threshold processing on a value corresponding to this obstacle height, it is determined whether or not there is an obstacle having a height that interferes with the traveling of the mobile robot 1. When an obstacle having a height that interferes with the traveling of the mobile robot 1 is detected and determined to be abnormal, an abnormal signal is output from the communication unit 20 described later, and the movement control unit 9 stops the mobile robot 1. Or a predetermined process such as deceleration is performed. The obstacle determination unit 19 determines an abnormality using the obstacle map. Specific examples will be described later.

(8) Imaging Unit The imaging unit 7 is a unit that is mounted on the upper surface of the mobile robot 1 and images the surroundings of the mobile robot 1. In this example, a plurality of cameras are arranged outward in the circumferential direction so as to cover the entire circumference.

(9) Communication unit The communication unit 20 is a wireless communication unit that transmits and receives signals to and from a remote monitoring center. When the mobile robot 1 detects an abnormality in the monitoring area, the communication unit 20 outputs an abnormality signal to the remote monitoring center by radio or the like. The communication unit 20 transmits the image captured by the imaging unit 7 and the position of the mobile robot 1 calculated by the self-position detection unit 13 to the remote monitoring center, and receives a control command signal transmitted from the monitoring center. To the control unit 21 described later.

(10) Control Unit The control unit 21 is a unit that comprehensively controls each component of the mobile robot 1 and is configured by a computer including a CPU and the like.

  In addition, in the configuration of each unit described above, the function that can be realized by computer processing may be realized by the same computer. For example, the road surface information extraction unit 12, the position calculation unit 15, the movement control unit 9, the road surface state determination unit 23, the obstacle determination unit 19, and the like may be realized by the same computer. The storage unit 17 may be realized by a memory of the computer, an external storage device, or the like.

3. Procedures for Information Processing in the Control System of the Mobile Robot and Operations Based on the Procedures The control operation during travel of the mobile robot 1 of the present example will be described below. First, the overall obstacle detection during travel of the mobile robot 1 of the present example will be described. An explanation will be given of the control procedure (FIG. 5), and the travel control of the mobile robot 1 performed by using the information acquired in the procedure of FIG. 5 will be explained (FIG. 6). Next, wet road surface detection control (FIG. 7) and obstacle detection control (FIG. 8) in the control procedure at the time of obstacle detection will be described in detail. In the following description using each flowchart, each step of the control procedure is indicated by a serial number starting with S.

(1) Overall control for obstacle detection (Figure 5)
FIG. 5 is a flowchart showing the entire obstacle detection procedure during travel of the mobile robot 1 of this example. In this procedure, when the wet road surface is detected in the wet road surface detection process (S01), the mobile robot is detected. A request for speed setting to lower the upper limit of the traveling speed of 1 is made, a threshold for determining that there is an obstacle is raised, and an obstacle detection process (S07) is performed based on a single scanning result by the laser sensor. Thus, the mobile robot of this example changes the obstacle determination logic depending on whether the road surface is wet or not. Here, when the presence or absence of an obstacle is detected, a request to stop / decelerate the mobile robot 1 is made according to the detection result. In this example, an example of the obstacle detection control is shown in FIGS. 8 and 9. However, the present invention is not limited to this, and the obstacle detection is based on the difference in distance values obtained by scanning the front road surface with the distance measuring sensor 16. Any process that determines the presence or absence of an object may be used.

S01: In the wet traveling road surface detection process, it is determined whether or not the traveling road surface is wet. Details of this subroutine are shown in FIG.
S02: If the traveling road surface is wet, proceed to S05. If there is no wetting, the process proceeds to S03.

S03: When the traveling road surface is not wet (NO in S02), the controller 21 is instructed to set the upper limit of the traveling speed to maxH. The upper limit maxH of the traveling speed indicates the upper limit of the traveling speed when the traveling road surface is not wet. In addition, wetting is detected because it is not preferable to perform speed control frequently when there are water puddles due to the unevenness of the road surface, and the wet and dry surface changes in the result of wet road surface judgment processing at short intervals. After that, the upper limit speed is not changed even if it is determined that the vehicle is dry until it has traveled a predetermined distance, or the position determined to be wet is stored on the obstacle map, and the mobile robot 1 travels to make it move on the map. You may make it restart the determination of a dry road surface after the position determined to be wet from a predetermined area disappears.
S04: As a threshold value (a value corresponding to the obstacle height) for determining that there is an obstacle according to the traveling road surface condition (no wetting), a threshold value thL that is relatively lower than that when the road surface is wet is set. Set. That is, since the error of the distance detected by the laser sensor 2 is relatively smaller on a dry traveling road surface than on a wet road surface, the upper limit of the traveling speed is relatively high (maxH) and it is determined that there is an obstacle. The threshold value at that time is relatively low (thL). The set threshold value thL is stored in the storage unit 17.

S05: When the traveling road surface is wet (YES in S02), the controller 21 is instructed to set the upper limit of the traveling speed to maxL (<maxH). The upper limit maxL of the traveling speed indicates the upper limit of the speed when the traveling road surface is wet. That is, when the traveling road surface is wet, the speed of the mobile robot 1 is decreased as compared with the case where the traveling road surface is not wet.
S06: A relatively high threshold value thH is set as a threshold value (a value corresponding to the obstacle height) for determining that there is an obstacle according to the traveling road surface condition (with wetness) as compared with the case where the road surface is not wet. To do. That is, since the error of the distance detected by the laser sensor 2 is relatively larger on the wet traveling road surface than the case where the distance is dry, the upper limit of the traveling speed is relatively lowered (maxL) and it is determined that there is an obstacle. The threshold value at that time is relatively high (thH). The set threshold value thH is stored in the storage unit 17.

  S07: An obstacle detection process (a distance difference detection method from the traveling road surface) is executed. This subroutine is shown in FIG. 8, and will be described in detail later with reference to FIG.

  S09: It is determined whether or not there is an obstacle in the obstacle detection process of S07. If there is an obstacle, the process proceeds to S10, and if not, the process proceeds to S14.

  S10: If there is an obstacle (YES in S09), it is determined whether this obstacle is in the stop area (see FIG. 4) in the obstacle map (S10). If there is an obstacle (YES in S10), S11. In step S12, the control unit 21 is instructed to stop the mobile robot 1. If not (NO in step S10), the process proceeds to step S12.

  S12: It is determined whether or not the detected obstacle is in the deceleration area (see FIG. 4) in the obstacle map. If there is (YES in S12), the control unit 21 is instructed to decelerate the mobile robot 1 in S13, and if not (NO in S12), the process proceeds to S14.

  S14: It is determined whether or not an instruction to stop the obstacle detection process is input from the control unit 21, and if not, the process returns to S01 and the above processing procedure is repeated, and if there is an instruction to stop, the process ends.

(2) Overall travel control (Fig. 6)
FIG. 6 shows a flowchart in the case where the travel control of the mobile robot 1 of this example is performed with one travel section between the instruction marker 4 and the instruction marker 4, while traveling on a prescribed travel route according to the initial setting. FIG. 5 shows an information processing procedure performed based on a travel speed setting request, a stop request, a deceleration request, etc., output in the above-described obstacle detection process (FIG. 5).

S51: The control unit 21 acquires the speed designated as maxH as the speed information of the current travel section from the route information stored in the storage unit 17. In the route information, two speeds maxH and maxL are stored as travel speeds for each travel section. The mobile robot 1 normally travels at a speed specified by maxH, and travels with a travel speed of maxL when a wet road surface is detected.
S52: The control unit 21 causes the mobile robot 1 to travel at the travel speed specified as the acquired maxH.

S53: The control unit 21 obtains information on the traveling speed (maxH set speed, maxL set speed, stop request, or deceleration request) output to the control unit 21 in the flow of FIG. 5 described above by the processing unit 18. To do.
S54: The control unit 21 determines whether or not there is a stop request in the information on the traveling speed from the processing unit 18. If there is a stop request (YES in S54), the traveling of the mobile robot 1 is stopped in S55. When the mobile robot 1 stops, the control unit 21 maintains the mobile robot 1 in a stopped state until a command to start traveling is received again.

  S56: If there is no stop request (NO in S54), it is determined whether or not a speed change is necessary based on information on the running speed from the processing unit 18 (hereinafter referred to as “designated speed”). The control unit 21 compares the designated speed with the current running speed, and decelerates to the designated speed if the current running speed is faster than the designated speed, and accelerates to the designated speed if the current running speed is slower than the designated speed. Run.

In other words, when the upper limit of the specified speed is increased or decreased (for example, when the road surface is changed from maxL when the road surface is wet to maxH when the road surface is dry or when it is changed from maxH when the road surface is dry to maxL when the road surface is wet) ) If the current traveling speed is the same as the upper limit of the specified speed, the vehicle will travel at the current traveling speed as it is. If the current traveling speed is slower than the upper limit of the specified speed, it will accelerate to the upper limit of the specified speed, and the current traveling speed will be specified. If it is faster than the upper limit of the speed, it will decelerate to the upper limit of the specified speed. The upper limit of the speed specified as maxH is the value of the traveling speed stored in advance in the route information of the storage unit 17 for each section, for example, 10 km / h, 6 km / h, etc., and specified as maxL The upper limit of the speed to be set is, for example, 3 km / h or less which is less than maxH.
In addition, when a deceleration request is made because the obstacle is in the deceleration area in the obstacle map, the vehicle is decelerated regardless of the travel speed request by maxH or maxL.

  S57: If the control unit 21 determines that the speed change is necessary by the process as described above (YES in S56), the speed is changed to the designated travel speed.

  S58: The control unit 21 determines whether or not the travel section in which the mobile robot 1 is traveling has ended. If not completed, the process returns to S53 and the above procedure is repeated. If the travel section has ended, the process returns to S51 to start travel control in the next travel section. Further, when the end point of the route is reached, the above control is terminated.

(3) Wet road surface detection control (Fig. 7)
FIG. 7 shows a specific flow of wet road surface detection processing by the laser sensor that is made into a subroutine in S01 of FIG.
S71: The road surface state determination unit 23 acquires data (sensor data) of the distance value y to the measurement point that reflects the laser beam by the output signal from the laser sensor 2. The laser sensor irradiates the traveling road surface about 3 m ahead in the range of the central angle close to 180 degrees to obtain reflected light (see FIG. 3). The laser sensor 2 obtains and outputs a distance value y from the time from laser light irradiation to reflected light detection.

  S72: The road surface state determination unit 23 selects N pieces of data corresponding to the front in the traveling direction of the mobile robot 1 (for example, 121 pieces of data corresponding to 60 degrees in front) from the sensor data.

S73: The road surface state determination unit 23 counts the number of sensor data in which the value of each sensor data (distance value y) is equal to or less than a predetermined value among the N data corresponding to the front in the traveling direction.
Here, the constant value is a numerical value slightly higher than the distance value obtained when the light is reflected on the road surface, and the obtained value of each sensor data (distance value y) is equal to or less than the constant value is a laser beam. Is reflected on the traveling road surface and returned to the laser sensor 2, which means that the reflected light is obtained from the portion of the traveling road surface where the laser light hits. In other words, the count number here means the number of laser beams reflected from the traveling road surface and returned to the laser sensor 2 out of N pieces of sensor data.
When the traveling road surface is wet, the laser light may be totally reflected on the traveling road surface and may not return to the laser sensor 2. In this case, the sensor data in the laser sensor 2 is evaluated as being unmeasurable or infinite. Then, it is determined that the sensor data value (distance value y) is not within a certain value (greater than a certain value). Alternatively, when the traveling road surface is wet, the laser light diffusely reflected on the traveling road surface and returned to the laser sensor 2 may be output as a large distance value significantly different from the distance value from the road surface in the laser sensor. Therefore, in this example, the sensor data indicating a significantly large distance value compared to the case where the light is reflected on the road surface is processed by assuming that the sensor data is based on the laser light reflected on the wet road surface.

  S74: The road surface state determination unit 23 determines whether the ratio of the count number to the number N of the sensor data is equal to or greater than a predetermined value (for example, 70%) set in advance.

  S75: When the ratio of the count number to the number N of the sensor data is equal to or greater than the predetermined value (YES in S74), it is determined that the road surface is dry.

  S76: If the ratio of the count to the total number N of sensor data is not equal to or greater than the predetermined value (NO in S74), it is determined that the road surface is wet.

  In the wet road surface detection control in this example, in the processing of a plurality of sensor data obtained by the laser sensor 2, a detection signal whose distance value is equal to or smaller than a certain value is regarded as being from a dry road surface, and the total number of counts is as follows. It is judged that the road surface is dry when the percentage of the road is greater than or equal to a predetermined value, and the road value is judged to be wet when the percentage is less than the predetermined value. If the sensor data is taken from a wet road surface, and the percentage of the total count is greater than or equal to a predetermined value, it is determined that the road surface is wet. It may be configured to determine that the road surface is dry.

(4) Obstacle detection control (Figs. 8 and 9)
This obstacle detection control is a method for detecting any obstacle present on a flat traveling road surface.

S81: In the sensor data for one cycle, those whose difference in distance value is equal to or less than a predetermined value between adjacent data are grouped and labeled.
FIG. 9 is a plot of sensor data of distance value y indicating each position detected by the laser sensor by scanning in one cycle in the same manner as in FIG. 10 described above, and the X axis is the front of the mobile robot 1. And the Y axis indicate distance values from the mobile robot 1. Although it is a continuous straight line in the figure, it is actually a set of measurement points, and the horizontal straight lines on both sides in the figure are data on a flat road surface, and the central convex part is placed on the road surface. This is data indicating the distance to the obstacle, and the continuous part of both indicates data by reflection from the side of the obstacle. Although not shown, the position of the laser sensor is the origin of the XY coordinates and is below in the figure.

  Here, labeling means classifying a plurality of data that are close in the y direction and arranged in the x direction in a permutation of sensor data as one set. In the example of FIG. Two horizontal straight lines and a central convex part are labeled. In the sensor data, it is preferable to exclude the data having a significantly large distance value as an object to be labeled. For example, the distance value is identified by a constant value used in the process of S73 of FIG. It is preferable that data whose value is equal to or less than a certain value is the target of the labeling process.

  S82: Focusing on one piece of labeled data (labeling data), is there labeling data consisting of K (for example, 10) or more measurement points on both sides in the X direction of the labeling data? Judge whether or not. The value of K is appropriately set in consideration of the total number of sensor data, the size of the obstacle to be detected, and the like.

  S83: If there are K or more data on both sides (YES in S82), it is determined whether or not the labeling data on both sides have substantially the same y coordinate value. Thus, it is determined whether the labeling data on both sides is based on the traveling road surface.

  S84: The difference between the average value of the y coordinate values of the focused labeling data and the average value of the y coordinate values of the labeling data on both sides is calculated. Thereby, a difference in distance value between the target detection object and the detection objects on both sides thereof is obtained. This distance difference corresponds to the height of the target detection object.

  S85: The difference calculated in S84 is greater than or equal to the obstacle determination threshold value (threshold value corresponding to the height of the obstacle: thL or thH) stored in the storage unit 17 in the control related to detection shown in FIG. It is determined whether or not. As shown in FIG. 5, the storage unit 17 stores a relatively high value thH as a value corresponding to the height if the road surface is wet, and the height if the road surface is not wet. Any of relatively low values thL is set as a threshold for obstacle determination as a corresponding value.

  S86: If the difference calculated in S84 is greater than or equal to the obstacle determination threshold (YES in S85), the noted labeling data is recognized as an obstacle and it is determined that there is an obstacle.

  If it is determined that there is an obstacle and if NO in S82, S83, and S85, respectively, it is determined whether or not the above processing has been performed for all labeling data, and if all are processed (YES in S87), this flow When the processing procedure is completed and the above processing is not performed for all the labeling data (NO in S87), the process returns to S82 and the above procedure is repeated focusing on the next labeling data.

  In the embodiment described above, road surface wetness information detected by a distance measuring sensor is used as control information for obstacle detection control. In other words, by changing the upper limit value of the running speed and the threshold value that is the criterion for obstacle detection according to the detection of wetness on the road surface, the obstacle detection logic is changed to reduce the possibility of false alarms and improve the judgment accuracy. Control was performed. However, the road surface wetness information obtained by the mobile robot of the present invention can be widely used in general mobile robot control other than obstacle detection control. For example, the travel speed or speed limit area (stop area or deceleration area) of the mobile robot is used. It is also possible to change the setting of the area), change the function of reading the guide means by the guide detection unit, change the setting of the imaging function of the camera for monitoring the surroundings, and the like.

FIG. 1 is a plan view of a monitoring area, which is an environment in which a mobile robot 1 according to an embodiment of the present invention is used, and a perspective view showing an appearance of the mobile robot 1. FIG. 2 is a functional block diagram showing a specific configuration of the mobile robot 1 of this example. FIG. 3A is a side view showing a geometric positional relationship between the laser sensor 2 and the measurement point in the mobile robot 1 of this example, and FIG. 3B is a scanning angle range Φ of the laser sensor 2. It is a top view which shows the sensing area (shaded area) etc. which are shown by. FIG. 4 is a diagram showing a map area registered as a map in which the position of the laser sensor installed in the mobile robot 1 is the origin (0, 0) in the storage unit 17 of the mobile robot 1 of this example. FIG. 5 is a flowchart showing the entire obstacle detection procedure in the travel control of the mobile robot 1 of this example. FIG. 6 shows a flowchart in the case where the travel between the instruction marker 4 and the instruction marker 4 is one travel section in the travel control of the mobile robot 1 of this example. FIG. 7 shows a specific flow of wet road surface detection processing by the laser sensor that is made into a subroutine in S01 of FIG. FIG. 8 is a flowchart showing the obstacle detection control based on the distance difference detection method from the road surface suitable for detecting any obstacle present on the flat road surface. FIG. 9 is a graph in which sensor data of a distance difference y indicating each position detected by a laser sensor in one cycle is plotted on an xy coordinate plane. FIG. 10 is a diagram showing, in a time series, states of obstacle detection during traveling in the mobile robot 1 having a basic structure that detects an obstacle while scanning a laser obliquely forward and downward while moving. At each time t to t + 4, the laser beam, the side view of the mobile robot 1 and the obstacle, and the distance difference between the detection target and the mobile robot 1 in the plane xy coordinate system screen with the position of the laser sensor 2 as the origin (see FIG. (Distance in the middle y direction) is expressed by a laser trajectory.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Mobile robot 2 ... Laser sensor as a ranging sensor 16 ... Ranging sensor 21 ... Control part 23 ... Road surface state determination part as a road surface state determination means

Claims (4)

A mobile robot that detects the wet state of a traveling road surface,
A distance measuring sensor that transmits a detection wave for distance measurement to the road surface and receives a reflected wave to measure a distance to the mobile robot;
Obstacle determination means for detecting an obstacle on the road surface based on distance data measured by the distance measuring sensor;
Road surface condition determining means for detecting a wet state of the road surface based on distance data outside a predetermined range measured by the distance measuring sensor or unmeasurable distance data;
A mobile robot characterized by comprising: The distance measuring sensor transmits a predetermined number of detection waves to the road surface and receives reflected waves,
The road surface condition judging means is wet if the ratio of the number of distance data outside the predetermined range or the distance data that cannot be measured to the total or part of the detected wave numbers transmitted is equal to or greater than a predetermined threshold. The mobile robot according to claim 1, which is determined as follows. The mobile robot according to claim 1, wherein the obstacle determination unit varies a logic for detecting an obstacle according to the determination by the road surface state determination unit. 4. The mobile robot according to claim 2, wherein the predetermined number of detection waves in the distance measuring sensor is a number necessary to scan a predetermined area of the road surface including at least the front in the traveling direction.

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