Wheel position acquisition device

Abstract

The goal is to improve the accuracy of acquiring the position of the object's wheels, even when the moving object is tilted relative to the object. [Solution] Information regarding the wheels is acquired in a first coordinate system, but by performing a coordinate transformation from the first coordinate system to a second coordinate system, information regarding the wheels in the second coordinate system is acquired. The first coordinate system is the coordinate system set for the vehicle information acquisition device of the moving object. The second coordinate system is the coordinate system set for the object or the position in which the object exists. In this way, even if information regarding the wheels is acquired in the first coordinate system, information regarding the wheels in the second coordinate system is acquired through coordinate transformation. As a result, even if the moving object is not directly facing the object, it becomes possible to accurately acquire the position of the object's wheels.

Description

Technical Field

[0001] The present invention relates to a wheel position acquisition device that acquires the position of a wheel of an object.

Background Art

[0002] Patent Document 1 describes a wheel position acquisition device provided in a conveyance system in which a conveyance robot conveys an object, and acquires the position of a wheel of the object. In the wheel position acquisition device, the conveyance robot approaches the object, and in that state, uses a 2D-LiDAR (2 Dimension - Light Detection and Ranging) provided in the conveyance robot to acquire the position of the wheel of the object.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Disclosure of the Invention

Problems to be Solved by the Invention

[0004] An object of the present invention is to improve the acquisition accuracy of the position of a wheel of an object even when a moving body is inclined with respect to the object. Means, actions, and effects for solving the problems

[0005] In the wheel position acquisition device described in the present invention, information regarding the wheel is acquired in a first coordinate system, and by performing coordinate conversion from the first coordinate system to a second coordinate system, information regarding the wheel in the second coordinate system is acquired. The first coordinate system is a coordinate system set for a vehicle information acquisition device of a moving body. The second coordinate system is a coordinate system set for an object or a position (area) where the object exists. As a result, even when the moving body is not directly facing the object or the area where the object exists, it is possible to accurately acquire the position of the wheel of the object.

Brief Description of the Drawings

[0006] [Figure 1] This diagram schematically shows an entire transport system, including a wheel position acquisition device, which is one embodiment of the present invention. [Figure 2] This is a plan view of the transport robot, which is a component of the above transport system. [Figure 3] This is a side view showing the above transport robot transporting a vehicle as its target object. [Figure 4] This diagram conceptually shows the area around the control device of the above-mentioned transport robot. [Figure 5] This diagram conceptually shows the structure of the control device, which is a component of the above-mentioned transport system. [Figure 6] This is a flowchart showing the wheel position acquisition program stored in the memory unit of the control device of the above transport system. [Figure 7] This is a plan view showing the above-mentioned transport robot and the object. [Figure 8] This diagram illustrates the execution of the wheel position acquisition program described above. [Figure 9] This diagram illustrates another execution step of the wheel position acquisition program described above. Embodiments of the Invention

[0007] A transport system including a wheel position acquisition device, which is one embodiment of the present invention, will be described in detail below with reference to the drawings. [Example 1]

[0008] The transport system, as shown in Figure 1, is installed in a predetermined work area. The transport system includes a plurality of mobile units 10 and a management device 12. The mobile units can be, for example, transport robots 10 that transport objects. The objects can be, for example, a vehicle to be transported c, as shown in Figure 3. Each of these transport robots 10 and the management device 12 are capable of wireless communication. The vehicle to be transported c is parked (waiting) in a parking space P (see Figure 7), which is a predetermined position within the work area.

[0009] As shown in Figure 2, the transport robot 10 has a shape that extends longitudinally along the axis Lr. The transport robot 10 includes a main body 20 and a trolley 22. The main body 20 is provided with left and right front wheels 24, and the trolley 22 is provided with left and right rear wheels 26. As shown in Figure 4, the main body 20 includes the left and right front wheels 24, a drive unit 27, a steering unit 28, a height adjustment unit 30, a control unit 32, etc. The drive unit 27 drives the left and right front wheels 24 and may include, for example, an electric motor. By controlling the electric motor, driving force or braking force can be applied to the left and right front wheels 24. The steering unit 28 steers the left and right front wheels 24 and may include at least one electric motor as a steering actuator. The steering actuator allows the left and right front wheels 24 to be steered in common or separately.

[0010] The height adjustment device 30 adjusts the height of the trolley section 22 and may include, for example, a fluid pressure cylinder as a height adjustment actuator. The height adjustment device 30 adjusts the height of the trolley section 22 between the submersion height and the transport height. The submersion height is the height at which the trolley section 22 can submerge (enter) beneath the body of the transported vehicle c. The transport height is the height at which the transported vehicle c is lifted and transported. The transport height is higher than the submersion height.

[0011] The bogie section 22 includes a base 36, a front section 38, a rear section 40, etc. The base 36 extends longitudinally along the axis Lr. The rear section 40 includes a main body 42, a clamping device 44, a 2D-LiDAR (2-dimensional Light Detection and Ranging) 46, left and right rear wheels 26, etc.

[0012] The main body 42 is fixedly mounted on the base 36. The clamping device 44 holds the wheels w of the transported vehicle c. The clamping device 44 includes pairs of arms 51 provided on the left and right sides of the main body 42, an arm rotation actuator 50 (see Figure 4) that drives the arm pairs 51, etc. The left and right arm pairs 51 each include a first arm 48 and a second arm 49. The arm rotation actuator 50 rotates the left and right first arms 48 and the left and right second arms 49 between a retracted position, which is a position (attitude) that is approximately parallel to the axis Lr, and a clamped position, which is a position (attitude) that protrudes in the width direction from the main body 42 and is approximately perpendicular to the axis Lr. The arm rotation actuator 50 can include, for example, a fluid pressure cylinder or an electric motor.

[0013] The 2D-LiDAR 46 is an example of a wheel information acquisition device and is positioned at the center of the rear end surface of the main body 42 (on the axis Lr). Light is shone onto the 2D-LiDAR 46 toward the rear of the transport robot 10, and the light reflected after hitting an object is received, thereby acquiring the relative positional relationship between the 2D-LiDAR 46 and the light reflection point on the object. The 2D-LiDAR 46 is also positioned to shine light below the body of the transported vehicle c. Therefore, the 2D-LiDAR 46 acquires point cloud data that includes information representing the relative positional relationship between the 2D-LiDAR 46 and each of the multiple points on the wheels (tires) of the transported vehicle c.

[0014] Point cloud data can be represented by the distance of a point from the origin in the x and y directions within the sensor coordinate system, which is the coordinate system set for the 2D-LiDAR46. The sensor coordinate system is defined with the origin being a point (x0L, y0L) on the 2D-LiDAR46, with the y-axis being the direction in which the axis of the 2D-LiDAR46 (the axis Lr of the transport robot 10) extends, and the x-axis being the direction perpendicular to the y-axis. Therefore, the position (relative positional relationship) of a point on the wheel in the sensor coordinate system is determined by the distance in the x and y directions from the origin of the point on the wheel. Thus, point cloud data can be considered to contain the positional data of each of multiple points on the wheel. In this embodiment, point cloud data is an example of information about the wheel.

[0015] The front section 38 includes the main body 54, a clamping device 56, a spacing adjustment device 58 (see Figure 4), etc. The main body 54 is held on the base 36 so as to be movable in the axial direction. The clamping device 56 includes a pair of arms 63 provided on the left and right sides of the main body 54, and an arm rotation actuator 62 (see Figure 4). The arm pairs 63 provided on the left and right sides each include a first arm 60 and a second arm 61, respectively. The arm rotation actuator 62 rotates the left and right second arms 61 between a retracted position and a clamped position. The left and right first arms 60 are always in the clamped position.

[0016] The spacing adjustment device 58 moves the main body 54 of the front part 38 closer to or further away from the rear part 40, and may include, for example, a fluid actuator. The spacing adjustment device 58 allows the spacing between the pair of clamping devices 44, 56 to be adjusted. The spacing between the pair of clamping devices 44, 56 can be adjusted, for example, to match the wheelbase of the transported vehicle c.

[0017] As shown in Figure 4, the control device 32 is primarily computer-based and includes an execution unit 70, a storage unit 71, an input / output unit 72, etc. The input / output unit 72 is connected to an RTK-GNSS receiver 66, a communication device 68, a 2D-LiDAR 46, etc., as well as a drive unit 27, a steering device 28, a height adjustment device 30, a spacing adjustment device 58, arm rotation actuators 50, 62, etc.

[0018] The RTK-GNSS (Real Time Kinematic Global Navigation Satellite System) receiver 66 acquires a two-dimensional position (latitude, longitude) based on the received GNSS signals. The two-dimensional position can be considered as the position in the coordinate system set on the earth. The coordinate system set on the earth is referred to as the global coordinate system (xG, yG) in the present embodiment. Also, according to the RTK-GNSS receiver 66, the position in the global coordinate system can be accurately acquired.

[0019] Therefore, for example, if RTK-GNSS receivers 66 are provided at two points separated from each other on the transport robot 10, based on the differences in the positions in these x-directions (one of the latitude direction and the longitude direction) and y-directions (the other of the latitude direction and the longitude direction), the inclination (which can be referred to as the azimuth angle) ΘL (see FIG. 7) of the axis Lr of the transport robot 10 in the yaw direction in the global coordinate system can be acquired. The azimuth angle ΘL can be considered as the inclination in the yaw direction with respect to the global coordinate system of the sensor coordinate system.

[0020] Note that the azimuth angle ΘL can also be acquired based on the position of one RTK-GNSS receiver 66, the relative positional relationship between the transport robot 10 and the target, etc., when there is a target with a known position in the global coordinate system within the work area. For example, the relative positional relationship between the transport robot 10 and the target can be acquired based on the relative positional relationship between the 2D-LiDAR 46 and the target acquired by the 2D-LiDAR 46.

[0021] Furthermore, if the RTK-GNSS receiver 66 is installed near the 2D-LiDAR 46, the 2D position of the 2D-LiDAR 46 in the global coordinate system can be directly acquired by the RTK-GNSS receiver 66. On the other hand, regardless of which part of the transport robot 10 the RTK-GNSS receiver 66 is installed on, the 2D position of the 2D-LiDAR 46 can be acquired based on the relative positional relationship between the RTK-GNSS receiver 66 and the 2D-LiDAR 46. The position of the 2D-LiDAR 46 in the global coordinate system corresponds to the position of the origin in the sensor coordinate system.

[0022] As shown in Figure 5, the management device 12 includes a control unit 80, which is primarily a computer. The control unit 80 includes an execution unit 81, a storage unit 82, an input / output unit 83, etc. A communication device 86, etc., is connected to the input / output unit 83. Information is transmitted and received wirelessly between the communication device 86 and the communication devices 68 of each of the multiple transport robots 10. In addition to the control unit 80, a separate storage device can be provided, separate from the storage unit 82.

[0023] In the transport system configured as described above, based on a command from the management device 12, the transport robot 10 moves to the parking space P, which is the location (area) where the vehicle to be transported c is waiting (parked), places the vehicle to be transported c on the trolley 22, and transports it to the destination. The transport robot 10 approaches the parking space P where the vehicle to be transported c is parked, stops at a position directly facing the vehicle to be transported c (parking space P), and acquires the position of the wheels w of the vehicle to be transported c (for example, the position of each of the four wheels on the front, rear, left, and right) using the 2D-LiDAR 46. The transport robot 10 moves the trolley 22 under the body of the vehicle to be transported c so that it does not interfere with the wheels w of the vehicle to be transported c, etc.

[0024] To be in a position to face something directly means to be directly opposite it. This means that the transport robot 10 is in a state (attitude) where its axis Lr and the center line of the transported vehicle c (or parking space P) are approximately on the same straight line.

[0025] However, as shown in Figure 7, the transport robot 10 does not necessarily stop in a position directly facing the transported vehicle c (parking space P), but may stop tilted in the yaw direction (around the vertical axis, in other words, in a plan view). In this state, point cloud data is acquired in the sensor coordinate system by the 2D-LiDAR 46, but the point cloud data is processed assuming that the transport robot 10 is directly facing the parking space P.

[0026] For example, from the position data of multiple points constituting the point cloud data acquired by 2D-LiDAR46, position data located within the pre-defined ranges of wheel frames DL1, DL2, DL3, and DL4 is extracted. Then, as shown in Figure 7, the value obtained by statistically processing the extracted point position data (xn, yn) is obtained as the wheel position Po. For example, the wheel position can be set as the average value of the x and y components of the point position data, or as the median value of the x and y components. Note that wheel frame D is a pre-defined range based on the estimated location of the wheels w of the transported vehicle c. Wheel frame D is pre-defined based on the wheel width, wheelbase, etc. of the transported vehicle c. The term wheel frame D is used collectively without distinguishing between wheel frames DL1, DL2, DL3, DL4, wheel frames DP1, DP2, DP3, DP4, etc.

[0027] However, as shown in Figure 7, when the transport robot 10 is tilted in the yaw direction relative to the transported vehicle c, the sensor coordinate system is shifted from the parking frame coordinate system (region coordinate system), which is determined by the parking frame P of the transported vehicle c. As a result, the wheel frames DL1, DL2, DL3, DL4 are also shifted from the wheel frames DP1, DP2, DP3, DP4 in the parking frame coordinate system. Therefore, when data located within the wheel frames DL1, DL2, DL3, DL4 is extracted from the position data of multiple points, the resulting data is the wheel position Po, making it difficult to accurately obtain the position of the wheel w.

[0028] If the wheel frame D (DL1, DL2, DL3, DL4) is set to a larger size, it is thought that it will be possible to extract position data corresponding to the wheel w in a good manner. However, there is a risk that points corresponding to objects other than the wheel w (for example, foreign objects, etc.) will also be extracted, and the accuracy of wheel position acquisition will not necessarily improve.

[0029] Therefore, in this embodiment, the sensor coordinate system is converted to the parking space coordinate system, point cloud data in the parking space coordinate system (xP, yP) is obtained based on the point cloud data in the sensor coordinate system, and the wheel position is obtained based on the point cloud data in the parking space coordinate system.

[0030] Information such as the inclination (azimuth angle) ΘP of the parking space coordinate system relative to the global coordinate system, the position of the origin of the parking space coordinate system in the global coordinate system (x0P, y0P), and the positions of wheel frames DP1, DP2, DP3, and DP4 are acquired and stored in advance by the management device 12.

[0031] In contrast, instead of using the parking space coordinate system, it is possible to use the object coordinate system, which is a coordinate system set for the parked transported vehicle c. However, it is assumed that the transported vehicle c is parked in a predetermined state (attitude, position, etc.) within the parking space. Therefore, the wheel position obtained using the parking space coordinate system and the wheel position obtained using the object coordinate system will be almost the same. This has been confirmed experimentally by the applicant and others.

[0032] Furthermore, when using an object coordinate system, the transport robot 10 must individually set the object coordinate system for each transported vehicle c and acquire the origin and azimuth angle ΘP each time. This increases the calculation time required to acquire wheel positions. In addition, it may be necessary to install sensors with high detection accuracy in order to set the object coordinate system.

[0033] In contrast, since the parking space P is pre-set, the origin, azimuth angle, etc. of the parking space coordinate system can be acquired and stored in advance. Therefore, the calculation time required to acquire the wheel position can be kept from becoming long. Furthermore, in the transport robot 10, there is no need to set the object coordinate system, and sensors with high detection accuracy for setting the object coordinate system become unnecessary.

[0034] Based on the above, in this embodiment, the parking space coordinate system is used to obtain the position of the wheel w. Alternatively, the object coordinate system can also be used.

[0035] The following explains how to obtain the wheel position. The point cloud data pL acquired by the 2D-LiDAR46 includes the position data (xn, yn) of each of the multiple points in the sensor coordinate system, as shown in equation (6) in Figure 9.

[0036] When the direction of the axis of the sensor coordinate system (e.g., the yL axis) is aligned with the direction of the axis of the parking space coordinate system (e.g., the yP axis), the rotation matrix MLP can be expressed using the value θ obtained by subtracting the azimuth angle ΘL of the sensor coordinate system from the azimuth angle ΘP of the parking space coordinate system, as shown in equation (2) of Figure 8.

[0037] The movement vector vG from the origin (x0L, y0L) in the sensor coordinate system to the origin (x0P, y0P) in the parking space coordinate system can be expressed as shown in equation 8(3) in Figure 8. However, the positions of both of these origins are in the global coordinate system. Therefore, the global coordinate system is transformed into the sensor coordinate system to obtain the movement vector in the sensor coordinate system. The rotation matrix MGL when the direction of the axis of the global coordinate system (e.g., the yG axis) is aligned with the direction of the axis yL of the sensor coordinate system can be expressed using the azimuth angle ΘL of the sensor coordinate system with respect to the global coordinate system, as shown in equation 8(1) in Figure 8.

[0038] Then, as shown in Figure 8(4), the movement vector vGL in the sensor coordinate system is obtained by multiplying the movement vector vG in the global coordinate system by the transpose of the rotation matrix MGL. The transpose matrix is ​​obtained by swapping the row elements and column elements of a matrix, as shown in equation 8(5).

[0039] Equation 9(7) in Figure 9 is a calculation formula for converting the sensor coordinate system to the parking space coordinate system and obtaining point cloud data in the parking space coordinate system. The part in parentheses in Equation 9(7) indicates the translation of the point cloud data due to the shift in the origin. By rotating this translated point cloud data using the transpose matrix of the rotation matrix MLP, point cloud data in the parking space coordinate system is obtained.

[0040] As shown in Figure 7, from the position data of multiple points included in this point cloud data, those located inside the wheel frames DP1, DP2, DP3, and DP4 set for the parking frame coordinate system are extracted. By statistically processing the position data (x, y) of the extracted multiple points, the position q of each wheel w (front, rear, left, and right) is obtained. The wheel position q, which is the position of each wheel w, is the position in the parking frame coordinate system and can be expressed as shown in equation (8) in Figure 9. Figure 7 shows the position Pc(xw4, yw4) of one wheel.

[0041] As shown in Figure 7, by converting the sensor coordinate system to the parking space coordinate system and using the point cloud data in the parking space coordinate system, the position of the wheel w can be obtained with high accuracy.

[0042] Next, as shown in equation (9) in Figure 9, the position q of the wheel w in the parking space coordinate system is converted to its position in the global coordinate system. In equation (9) of Figure 9, the operation in parentheses converts the parking space coordinate system to the sensor coordinate system, and the wheel position in the sensor coordinate system is obtained. By multiplying the obtained wheel position in the sensor coordinate system by the transpose of the inverse of the rotation matrix MGL, the wheel position Q in the global coordinate system is obtained. The inverse of the rotation matrix MGL is the matrix that, when multiplied by the rotation matrix MGL, becomes the identity matrix I, as shown in equation (10) of Figure 9.

[0043] In this way, by acquiring wheel position data Q in the global coordinate system, it becomes easier to control the movement of the transport robot 10. In this embodiment, the posture of the transport robot 10 is corrected so that the yP axis of the parking space coordinate system and its own central axis Lr are positioned almost on the same line, and in that state, the trolley section 22 is moved under the transported vehicle c. As a result, interference with the wheels w of the transported vehicle c is made less likely when the trolley section 22 moves under, and failures are made less likely.

[0044] In this embodiment, the wheel position acquisition program, represented by the flowchart in Figure 6, is executed in the control device 32 of the transport robot 10. This program is executed before the transport robot 10 places the vehicle c to be transported on it. In step 1 (hereinafter abbreviated as S1; the same applies to other steps), the control device 12 supplies the transport robot 10 with information such as the azimuth angle ΘP and the position of the origin (xOP, yOP) of the parking space coordinate system. In S2, the azimuth angle ΘL and the position of the origin (x0L, y0L) of the sensor coordinate system are obtained based on the GNSS signals received by the RTK-GNSS receiver 66. In S3, a rotation matrix MLP is obtained to match the orientation of the axis of the sensor coordinate system with the orientation of the axis of the parking space coordinate system. In S4, the movement vector vG of the origin is obtained according to equations (4) and (5) in Figure 8 and converted to the sensor coordinate system (vGL).

[0045] Next, in S5, the 2D-LiDAR46 acquires point cloud data pL, which includes the position data of each of several points on the wheel. In S6, the sensor coordinate system is transformed into the parking space coordinate system according to equation 9(7) in Figure 9, and point cloud data pLP in the parking space coordinate system is acquired. In S7, wheel frames DP1, DP2, DP3, and DP4 are set in the parking space coordinate system, and in S8, position data located inside each of the wheel frames DP1, DP2, DP3, and DP4 is extracted from the position data of several points included in the point cloud data pLP in the parking space coordinate system. In S9, the wheel position q in the parking space coordinate system is obtained by statistically processing the extracted position data.

[0046] In this embodiment, the wheel position acquisition device is configured by the control device 32, etc. The sensor coordinate system corresponds to the first coordinate system, and the parking space coordinate system corresponds to the second coordinate system. Furthermore, S5 corresponds to the wheel information acquisition process, S7 corresponds to the coordinate transformation process, and S8 and S9 correspond to the wheel position acquisition process.

[0047] In the above embodiment, the wheel position acquisition program was executed in the control device 32 of the transport robot 10, but it may also be executed in the control unit 80 of the management device 12. In that case, information about the sensor coordinate system acquired by the transport robot 10 (by the RTK-GNSS receiver 66, etc.) and point cloud data acquired by the 2D-LiDAR 46 are supplied from the transport robot 10 to the management device 12.

[0048] Furthermore, in the above embodiment, the 2D-LiDAR 46 corresponds to the wheel information acquisition device, but the wheel information acquisition device may also include a camera.

[0049] Furthermore, the present invention can be implemented in various modified and improved forms based on the knowledge of those skilled in the art. [Explanation of symbols]

[0050] 10: Transport robot 10: Management device 32: Control device 46: 2D-LiDAR 66: RTK-GNSS receiver 68: Communication device 80: Control unit 86: Communication device Patentable invention

[0051] (1) A wheel position acquisition device provided on a moving body, which includes a wheel information acquisition device that acquires information about the wheels of an object in a first coordinate system which is its own coordinate system, and converts the information about the wheels in the first coordinate system acquired by the wheel information acquisition device into information about the wheels in a second coordinate system which is a coordinate system set for the object or the area in which the object exists, and acquires the position of the wheels of the object in the second coordinate system.

[0052] (2) The wheel information acquisition device acquires point cloud data, which includes the position data of each of a plurality of points on the wheel, as information about the wheel. The wheel position acquisition device according to item (1), wherein the wheel position acquisition device converts the point cloud data in the first coordinate system into point cloud data in the second coordinate system to acquire the position of the wheel.

[0053] (3) The wheel position acquisition device according to item (2), wherein the wheel position acquisition device extracts position data of points located within the wheel frame, which is the range in which the wheel of the object is thought to exist, from among the position data of each of the multiple points included in the point cloud data in the second coordinate system, and obtains the position of the wheel by statistically processing the multiple extracted position data.

[0054] For example, the wheel's position can be determined by using the average of the x and y components of the positional data for each of the extracted points, or by using the median value.

[0055] (4) A wheel position acquisition device according to any one of items (1) to (3), wherein the wheel position acquisition device converts the point cloud data in the first coordinate system into point cloud data in the second coordinate system based on a movement vector from the origin of the first coordinate system to the origin of the second coordinate system and a rotation angle from the first coordinate system to the second coordinate system.

[0056] The point cloud data is translated and rotated in the direction determined by the movement vector.

[0057] (5) The movement vector is obtained based on the position of the origin of the first coordinate system and the position of the origin of the second coordinate system in a reference coordinate system which is a predetermined coordinate system. The wheel position acquisition device according to item (4), wherein the rotation angle from the first coordinate system to the second coordinate system is acquired based on the azimuth angle of the first coordinate system and the azimuth angle of the second coordinate system in the reference coordinate system.

[0058] In the above embodiment, the reference coordinate system corresponds to the global coordinate system. Furthermore, the azimuth angle can be obtained, for example, as the inclination angle of the yL axis of the first coordinate system with respect to the yG axis of the reference coordinate system, and as the inclination angle of the yP axis of the second coordinate system with respect to the yG axis of the reference coordinate system.

[0059] (6) The wheel position acquisition device according to item (5), wherein the wheel position acquisition device converts the movement vector in the reference coordinate system into a movement vector in the first coordinate system, translates the information regarding the wheel according to the converted movement vector, and then rotates it.

[0060] (7) The wheel position acquisition device according to any one of items (1) to (6), wherein the wheel position acquisition device is provided in a transport system in which the moving body holds the wheels of the object and transports the object.

[0061] (8) A wheel information acquisition step in which information about the wheels of an object is acquired by a sensor installed on the moving body, A coordinate transformation step that converts information about the wheel in a first coordinate system, which is a coordinate system set for the sensor, into information in a second coordinate system, which is a coordinate system set for the object or the region in which the object exists; A wheel position acquisition step, which involves acquiring the position of the wheel based on the information about the wheel in the second coordinate system, A method for obtaining wheel position, including the wheel position.

[0062] The wheel position acquisition method may employ any of the technical features described in section (2) through (7). Furthermore, the wheel position acquisition method is performed in a wheel position acquisition device. The sensor corresponds to a wheel information acquisition device.

[0063] (9) A wheel position acquisition device as described in any one of items (1) through (7), A mobile body movement control unit moves the mobile body toward the object by correcting the posture of the mobile body so that the central axis of the mobile body approaches the central axis of the object, which is obtained based on the position of the wheels obtained by the wheel position acquisition device, and then moving the mobile body toward the object. A work system that includes this.

[0064] The mobile unit control unit can be considered to include parts that control the drive unit 27, steering unit 28, etc. of the control device 32, or it can be considered to include the above-mentioned parts of the control device 32 and the parts that create and output commands to the transport robot 10 from the control unit 80 of the management device 12.

Claims

1. A wheel position acquisition device provided in a transport system that transports an object by holding the wheels of the object, the wheel position acquisition device, The wheel position acquisition device includes a wheel information acquisition device provided on the moving body that acquires information about the wheels of the object in a first coordinate system which is its own coordinate system, and converts the information about the wheels in the first coordinate system acquired by the wheel information acquisition device into information about the wheels in a second coordinate system which is a coordinate system set for the object or the area in which the object exists, and acquires the position of the wheels of the object in the second coordinate system.

2. The wheel information acquisition device acquires point cloud data, which includes the position data of each of a plurality of points on the wheel, as information about the wheel. The wheel position acquisition device according to claim 1, wherein the wheel position acquisition device converts the point cloud data in the first coordinate system into point cloud data in the second coordinate system, extracts the position data of points located within the wheel frame, which is the range in which the wheel of the object is thought to exist, from among the position data of a plurality of points included in the converted point cloud data in the second coordinate system, and obtains the position of the wheel by statistically processing the extracted plurality of position data.

Images