Vehicle evaluation method and system for robot vehicle carrying, storage medium and computer

Abstract

The invention relates to the technical field of vehicle carrying robots. The method comprises the following steps: acquiring vehicle bottom laser radar data of a to-be-carried vehicle through a laser radar; segmenting and intercepting the bottom laser radar data of the to-be-carried vehicle according to the distance between the laser radar and the ground to obtain corresponding wheel section segmentation laser radar point cloud data; performing point cloud segmentation on the wheel section segmentation laser radar point cloud data to obtain corresponding four pieces of wheel point cloud data, and determining corresponding wheel coordinate information according to the wheel point cloud data; according to the coordinate information of the four wheels of the to-be-carried vehicle, the corresponding wheel track and the vehicle posture are determined; according to the size of the vehicle carrying robot, the wheel track and the vehicle posture, whether the vehicle carrying robot can pass through the to-be-carried vehicle or not is judged; the vehicle data information of the to-be-carried vehicle on the parking space of the parking lot can be obtained in real time, and the vehicle posture information and the vehicle chassis of the to-be-carried vehicle are obtained, so that an adaptive vehicle carrying robot is arranged to carry the vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of robot transport, and more particularly to a vehicle evaluation method, system, storage medium and computer for robot transport. Background Art

[0002] At present, in the process of transporting vehicles, a vehicle moving robot is usually used to move the vehicle, such as a vehicle carrying plate type, a comb tooth type or a clamping wheel type vehicle moving robot.

[0003] Most of the existing car moving robots are equipped with laser radars. When a car needs to be moved, the car moving robot is moved in front of the vehicle to be moved, and the vehicle data information of the vehicle to be moved is obtained through the laser radar. The vehicle data information is used to determine whether the car moving robot can pass through the chassis of the car and enter the bottom of the car to move the transported vehicle. However, since the height of the bottom of vehicles of different models is different, and the height of the body of the car moving robot is certain, the chassis of the vehicle to be moved is often too low, making it impossible for the car moving robot to carry out the transport operation under the vehicle, and the robot can only rearrange a new robot to carry out the vehicle transport operation. For this reason, we propose a vehicle evaluation method, system, storage medium and computer for robot car moving. Summary of the invention

[0004] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a vehicle assessment method, system, storage medium and computer for robot vehicle handling to solve the technical problems existing in the above-mentioned background technology.

[0005] The above technical objectives of the present invention are achieved through the following technical solutions: A vehicle evaluation method for robot vehicle handling, comprising:

[0006] Acquire the bottom lidar data of the vehicle to be transported through lidar;

[0007] Segment and intercept the laser radar data of the bottom of the vehicle to be transported according to the distance between the laser radar and the ground, and obtain corresponding wheel cross-section segmentation laser radar point cloud data;

[0008] Performing point cloud segmentation on the wheel cross-section segmentation laser radar point cloud data to obtain corresponding four wheel point cloud data, and determining corresponding wheel coordinate information according to the wheel point cloud data;

[0009] Determine the corresponding wheelbase and vehicle posture according to the four wheel coordinate information of the vehicle to be transported;

[0010] According to the size of the vehicle moving robot, the wheelbase and the vehicle posture, it is determined whether the vehicle moving robot can pass through the vehicle to be moved.

[0011] Optionally, the laser radar can be flipped and installed on the ground of the parking area of ​​the vehicle to be transported through a flipping mechanism, and is located at the bottom of the vehicle to be transported; the wheels, chassis of the vehicle to be transported, and the ground of its parking area are all within the field of view of the laser radar to obtain the laser radar data of the bottom of the vehicle.

[0012] Optionally, determining corresponding wheel coordinate information according to the wheel point cloud data includes:

[0013] The wheel coordinate information is clustered and segmented according to the Euclidean distance, and the wheel point cloud data is grouped according to the distance between points to form 4 clusters of point cloud data representing the wheels;

[0014] The point cloud data in each cluster is traversed and averaged to obtain the corresponding four wheel coordinate information.

[0015] Optionally, the four wheel coordinate information of the vehicle to be transported determines the corresponding wheelbase and vehicle posture, including:

[0016] Select any three wheel coordinates from the four wheel coordinates, calculate the distance between the two coordinates, and sort them according to the distance values ​​to obtain the wheelbase, wheelbase, and the longest distance line segment; the shortest distance line segment represents the wheelbase, and the middle distance line segment represents the wheelbase;

[0017] The center coordinate value of the line segment with the longest distance is calculated based on the coordinates of the two end points of the line segment, which is the center coordinate (x, y) of the vehicle to be transported;

[0018] The vehicle posture angle θ of the vehicle to be transported based on the radar coordinate system is obtained according to the coordinates of the two end points of the wheelbase, and the vehicle posture coordinates (x, y, θ) of the vehicle to be transported are obtained.

[0019] Optionally, it is characterized in that it also includes: perturbing the vehicle posture coordinates according to a preset disturbance rule, and obtaining the vehicle posture disturbance coordinates (x±a, y, θ±b) after the disturbance, where a is the disturbance error of the vehicle posture coordinate x; b is the disturbance error of the vehicle posture angle θ.

[0020] Optionally, judging whether the transporting robot can pass through the vehicle to be transported according to the size of the transporting robot, the wheelbase and the vehicle posture includes:

[0021] Obtain the length and width dimensions of the robot and its handling posture, and express its handling posture as a linear equation of y=kx+c, where k is a variable and c can be a or b; through the formula Calculate the distance value d of all radar data points;

[0022] Traversing the straight line equation y=kx+c corresponding to the disturbance coordinates (x±a, y, θ±b) of the vehicle posture after the disturbance is added, when the distance values ​​of all radar data points satisfy that d is greater than the half-width of the vehicle moving robot, the robot can pass through the chassis of the vehicle to be transported, enter the bottom of the transport vehicle, and perform transport operations on the transport vehicle.

[0023] The present invention also provides a vehicle assessment system for robot vehicle handling, comprising:

[0024] A data acquisition module, used to acquire the vehicle bottom lidar data of the vehicle to be transported through the lidar;

[0025] A data segmentation module is used to segment and intercept the laser radar data of the bottom of the vehicle to be transported according to the distance between the laser radar and the ground, and obtain the corresponding wheel cross-section segmentation laser radar point cloud data;

[0026] A coordinate calculation module, used to perform point cloud segmentation on the wheel cross-section segmentation laser radar point cloud data to obtain corresponding four wheel point cloud data, and determine corresponding wheel coordinate information according to the wheel point cloud data;

[0027] Coordinate information processing, used to determine the corresponding wheelbase and vehicle posture according to the four wheel coordinate information of the vehicle to be transported;

[0028] The data comparison module is used to determine whether the vehicle moving robot can pass through the vehicle to be moved according to the size of the vehicle moving robot, the wheelbase and the vehicle posture.

[0029] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described above are implemented.

[0030] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method described above when executing the computer program.

[0031] To sum up, the present invention has the following beneficial effects: it can acquire the vehicle data information of the vehicle to be transported in the parking space of the parking lot in real time, obtain the vehicle posture information and vehicle chassis of the vehicle to be transported, so as to arrange an adapted vehicle moving robot to carry out vehicle transport, and avoid the situation where the chassis of the vehicle to be transported is too low, causing the vehicle moving robot to be unable to carry out the transport operation under the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic flow chart of a vehicle evaluation method for robot vehicle moving provided by the present invention;

[0033] Figure 2is a schematic diagram of wheel cross-section segmentation laser radar point cloud data in the present invention;

[0034] Figure 3 It is a structural block diagram of a vehicle evaluation system for robot vehicle handling provided by the present invention;

[0035] Figure 4 It is a diagram of the internal structure of a computer device in an embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings. Several embodiments of the present invention are shown in the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein.

[0037] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. The terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features.

[0038] In the present invention, unless otherwise clearly specified and limited, the first feature being "above" or "below" the second feature may include the first and second features being in direct contact, or may include the first and second features being in contact not directly but through another feature between them. Moreover, the first feature being "above", "above" and "above" the second feature includes the first feature being directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. The first feature being "below", "below" and "below" the second feature includes the first feature being directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature. The terms "vertical", "horizontal", "left", "right", "above", "below" and similar expressions are for illustrative purposes only, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0039] The present invention is described in detail below in conjunction with the accompanying drawings and embodiments.

[0040] The present invention provides a vehicle evaluation method for robot vehicle handling, such as Figure 1 As shown, including:

[0041] S1. Obtaining the bottom lidar data of the vehicle to be transported through lidar;

[0042] S2, segmenting and intercepting the laser radar data of the bottom of the vehicle to be transported according to the distance between the laser radar and the ground, and obtaining corresponding wheel cross-section segmentation laser radar point cloud data;

[0043] S3, performing point cloud segmentation on the wheel cross-section segmentation laser radar point cloud data to obtain corresponding four wheel point cloud data, and determining corresponding wheel coordinate information according to the wheel point cloud data;

[0044] S4, determining the corresponding wheelbase and vehicle posture based on the four wheel coordinate information of the vehicle to be transported;

[0045] S5. Determine whether the vehicle moving robot can pass through the vehicle to be moved based on the size of the vehicle moving robot, the wheelbase and the vehicle posture.

[0046] In practical applications, a laser radar is installed on the bottom surface of each parking space in the parking lot so as to obtain the laser radar data of the bottom of the vehicle to be transported in each parking space through the laser radar. Each laser radar can be flipped and protruded and installed on the ground of the parking space in the parking lot, and has a certain height. The horizontal height range between the radar and the ground of the parking space is the height range of the horizontal section of the wheel, and the laser radar point cloud data of the geometric information of the horizontal section of the wheel in this height range is intercepted and saved, such as Figure 2 As shown; in the process of obtaining the wheel section segmentation lidar point cloud data, the wheel horizontal section height range is synchronously compared with the body height of the car handling robot.

[0047] Furthermore, the laser radar can be flipped and installed on the ground of the parking area of ​​the vehicle to be transported through a flipping mechanism, and is located at the bottom of the vehicle to be transported; the wheels, chassis of the vehicle to be transported, and the ground of its parking area are all within the field of view of the laser radar to obtain the laser radar data of the bottom of the vehicle.

[0048] In actual applications, the laser radar is installed on the ground of the vehicle parking space through a flipping mechanism. It is made of high-strength steel and has good load-bearing capacity and stability. When installed on the ground, it can withstand heavy objects such as cars without deformation. The laser radar is mainly used to observe the vehicle chassis. The vehicle chassis detection device is a flipping mechanism, which is generally installed under the ground. There is a flipping process during work, and the radar will move with the flipping mechanism. When chassis detection is required, the flipping mechanism moves 90° clockwise, and the radar is exposed on the ground for chassis detection. When chassis detection is not required, the flipping mechanism moves 90° counterclockwise, and the radar is hidden under the ground. At the same time, the flipping mechanism blocks the gap, is flush with the ground and plays a supporting role, making the ground flat and the handling robot can pass normally.

[0049] Further, determining corresponding wheel coordinate information according to the wheel point cloud data includes:

[0050] The wheel coordinate information is clustered and segmented according to the Euclidean distance, and the wheel point cloud data is grouped according to the distance between points to form 4 clusters of point cloud data representing the wheels;

[0051] The point cloud data in each cluster is traversed and averaged to obtain the corresponding four wheel coordinate information.

[0052] In practical applications, since the input radar data is only wheel data (consisting of four point clusters separated by a large distance), the EuclidianClusterExtraction class in PCL is used for point cloud segmentation. EuclidianClusterExtraction is a clustering segmentation based on Euclidean distance. The point cloud is grouped according to the distance between points to form multiple clusters. When the number of clusters formed is 4, the wheel segmentation is successful. Each cluster represents the point cloud data of a wheel. The point cloud data in each cluster is traversed and the average is calculated. The obtained coordinates are used as the approximate coordinates of the wheel, so the coordinate information of four wheels is obtained.

[0053] Furthermore, the four wheel coordinate information of the vehicle to be transported determines the corresponding wheelbase and vehicle posture, including:

[0054] Select any three wheel coordinates from the four wheel coordinates, calculate the distance between the two coordinates, and sort them according to the distance values ​​to obtain the wheelbase, wheelbase, and the longest distance line segment; the shortest distance line segment represents the wheelbase, and the middle distance line segment represents the wheelbase;

[0055] The center coordinate value of the line segment with the longest distance is calculated based on the coordinates of the two end points of the line segment, which is the center coordinate (x, y) of the vehicle to be transported;

[0056] The vehicle posture angle θ of the vehicle to be transported based on the radar coordinate system is obtained according to the coordinates of the two end points of the wheelbase, and the vehicle posture coordinates (x, y, θ) of the vehicle to be transported are obtained.

[0057] In practical applications, three wheel coordinate information are randomly selected from the four wheel coordinate information (always forming a triangle), and the distance between the two is calculated, and the distance is sorted according to the size of the distance. The smallest distance is the wheelbase, and the middle distance is the wheelbase; because the distribution of the wheels is always rectangular, any three points always form a right triangle, and the length rule remains unchanged; after the sorting in the previous step, the longest distance line segment (the hypotenuse of the right triangle) is basically through the center of the vehicle, and the center of the line segment is basically consistent with the center of the vehicle (the midpoint of the hypotenuse of the right triangle is the center of the rectangle); therefore, the midpoint coordinate value is calculated according to the endpoint coordinate values ​​of the line segment, which is the vehicle center coordinate (x, y); according to the wheelbase obtained in the previous step (distance sorting), the slope of the wheelbase indicates the direction of the vehicle, and the axle slope is obtained using the two end points of the wheelbase (based on the radar coordinate system), and the axle slope obtained can be used to represent the vehicle attitude angle (θ) of the vehicle based on the radar coordinate system; the vehicle attitude coordinates (x, y, θ) of the vehicle to be transported are obtained.

[0058] Furthermore, it also includes: disturbing the vehicle posture coordinates according to a preset disturbance rule, and obtaining the vehicle posture disturbance coordinates (x±a, y, θ±b) after adding the disturbance, wherein a is the disturbance error of the vehicle posture coordinate x; b is the disturbance error of the vehicle posture angle θ.

[0059] Further, judging whether the transporting robot can pass through the vehicle to be transported according to the size of the transporting robot, the wheelbase and the vehicle posture includes:

[0060] Obtain the length and width dimensions of the robot and its handling posture, and express its handling posture as a linear equation of y=kx+c, where k is a variable and c can be a or b; through the formula Calculate the distance value d of all radar data points;

[0061] Traversing the straight line equation y=kx+c corresponding to the disturbance coordinates (x±a, y, θ±b) of the vehicle posture after the disturbance is added, when the distance values ​​of all radar data points satisfy that d is greater than the half-width of the vehicle moving robot, the robot can pass through the chassis of the vehicle to be transported, enter the bottom of the transport vehicle, and perform transport operations on the transport vehicle.

[0062] In practical applications, the posture information of the vehicle is known. When the handling robot crosses the vehicle to be handled, the posture of the handling robot will continue to approach the posture of the vehicle to be handled. Therefore, the posture of the vehicle to be handled will be the posture of the handling robot when it is under the vehicle. The posture can be expressed as a linear equation of y=kx+c; since the vehicle posture is estimated using the wheel point cloud, it is necessary to add a certain disturbance, where the disturbance has three directions, namely, the wheelbase direction, the wheelbase direction, and the vehicle direction. Since the handling robot works in the mode of crossing the vehicle to be handled, because the disturbance in the wheelbase direction has little effect on the feasible domain judgment, the vehicle coordinates (x, y, θ) are changed to (x±a, y, θ±b) by adding disturbances in the wheelbase direction and the vehicle direction; k is a variable, and c can be the value of the disturbance error a or b; the linear equation that can be solved by k and b means that the handling robot can pass through the vehicle chassis and enter the bottom of the vehicle to perform the handling operation;

[0063] To ensure that the handling robot does not collide with the vehicle to be handled, that is, the size of the handling robot is smaller than the chassis size of the vehicle to be handled, the height dimension has been processed in the radar data segmentation process, and the length and width dimensions remain to be considered; the handling robot is expressed in the form of y=kx+c, which changes the collision problem into a point-to-line problem, which can be expressed as The straight line represents the center axis of the handling robot, so all radar data points need to satisfy d greater than the half-width of the handling robot, where the half-width refers to half of the length or width of the handling robot; the radius traverses the straight line equation (y=kx+b) corresponding to the vehicle coordinates (x±a, y, θ±b). When there is a certain posture corresponding to all radar data points satisfying d>half-width of the handling robot, it means that the handling robot can pass through the chassis of the vehicle with the handling vehicle and perform handling operations on the vehicle at the bottom of the vehicle.

[0064] A vehicle assessment method for robot vehicle moving of the present invention can obtain vehicle data information of a vehicle to be moved in a parking space in a parking lot in real time, and obtain vehicle posture information and vehicle chassis of the vehicle to be moved, so as to arrange an adapted vehicle moving robot to move the vehicle, thereby avoiding the situation where the chassis of the vehicle to be moved is too low, causing the vehicle moving robot to be unable to carry out the moving operation under the vehicle.

[0065] like Figure 3 As shown, the present invention also provides a vehicle assessment system for robot vehicle handling, comprising:

[0066] S10, a data acquisition module, used to acquire the bottom lidar data of the vehicle to be transported through the lidar;

[0067] S20, a data segmentation module, used to segment and intercept the laser radar data of the bottom of the vehicle to be transported according to the distance between the laser radar and the ground, and obtain corresponding wheel cross-section segmentation laser radar point cloud data;

[0068] S30, a coordinate calculation module, used to perform point cloud segmentation on the wheel cross-section segmentation laser radar point cloud data to obtain corresponding four wheel point cloud data, and determine corresponding wheel coordinate information according to the wheel point cloud data;

[0069] S40, coordinate information processing, for determining the corresponding wheelbase and vehicle posture according to the four wheel coordinate information of the vehicle to be transported;

[0070] S50, a data comparison module, used to determine whether the vehicle moving robot can pass through the vehicle to be moved according to the size of the vehicle moving robot, the wheelbase and the vehicle posture.

[0071] The specific definition of the vehicle assessment system for robot moving vehicles can be found in the definition of the vehicle assessment method for robot moving vehicles mentioned above, which will not be repeated here; each module of the vehicle assessment method system for robot moving vehicles can be implemented in whole or in part by software, hardware and their combination. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0072] In one embodiment, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-mentioned vehicle assessment method for robot vehicle moving.

[0073] In one embodiment, the present invention further provides a computer device, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus; wherein the processor of the computer device is used to provide computing and control capabilities; the memory of the computer device includes a non-volatile storage medium and an internal memory; the non-volatile storage medium stores an operating system, a computer program and a database; the internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium; the network interface of the computer device is used to communicate with an external terminal through a network connection; when the computer program is executed by the processor, a vehicle evaluation method for robot vehicle handling is implemented.

[0074] Those skilled in the art will understand that Figure 4The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0075] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0076] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0077] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A vehicle assessment method for robot vehicle handling, characterized in that: include: Acquire the bottom lidar data of the vehicle to be transported through lidar; Segment and intercept the laser radar data of the bottom of the vehicle to be transported according to the distance between the laser radar and the ground, and obtain corresponding wheel cross-section segmentation laser radar point cloud data; Performing point cloud segmentation on the wheel cross-section segmentation laser radar point cloud data to obtain corresponding four wheel point cloud data, and determining corresponding wheel coordinate information according to the wheel point cloud data; Determine the corresponding wheelbase and vehicle posture according to the four wheel coordinate information of the vehicle to be transported; According to the size of the vehicle moving robot, the wheelbase and the vehicle posture, it is determined whether the vehicle moving robot can pass through the vehicle to be moved.

2. A vehicle assessment method for robot vehicle handling according to claim 1, characterized in that: The laser radar can be flipped and installed on the ground of the parking area of ​​the vehicle to be transported through a flipping mechanism, and is located at the bottom of the vehicle to be transported; the wheels, chassis of the vehicle to be transported, and the ground of the parking area are all within the field of view of the laser radar to obtain the laser radar data of the bottom of the vehicle.

3. A vehicle assessment method for robot vehicle handling according to claim 1, characterized in that: The determining corresponding wheel coordinate information according to the wheel point cloud data includes: The wheel coordinate information is clustered and segmented according to the Euclidean distance, and the wheel point cloud data is grouped according to the distance between points to form 4 clusters of point cloud data representing the wheels; The point cloud data in each cluster is traversed and averaged to obtain the corresponding four wheel coordinate information.

4. A vehicle assessment method for robot vehicle handling according to claim 3, characterized in that: The four wheel coordinate information of the vehicle to be transported determines the corresponding wheelbase and vehicle posture, including: Select any three wheel coordinates from the four wheel coordinates, calculate the distance between the two coordinates, and sort them according to the distance values ​​to obtain the wheelbase, wheelbase, and the longest distance line segment; the shortest distance line segment represents the wheelbase, and the middle distance line segment represents the wheelbase; The center coordinate value of the line segment with the longest distance is calculated based on the coordinates of the two end points of the line segment, which is the center coordinate (x, y) of the vehicle to be transported; The vehicle posture angle θ of the vehicle to be transported based on the radar coordinate system is obtained according to the coordinates of the two end points of the wheelbase, and the vehicle posture coordinates (x, y, θ) of the vehicle to be transported are obtained.

5. A vehicle assessment method for robot vehicle handling according to claim 4, characterized in that: Also includes: The vehicle posture coordinates are disturbed according to the preset disturbance rules, and the vehicle posture disturbance coordinates after the disturbance are obtained (x±a, y, θ±b), where a is the disturbance error of the vehicle posture coordinate x; b is the disturbance error of the vehicle posture angle θ.

6. A vehicle assessment method for robot vehicle handling according to claim 5, characterized in that: The determining, based on the size of the vehicle handling robot, the wheelbase and the vehicle posture, whether the vehicle handling robot can pass through the vehicle to be handled includes: Obtain the length and width dimensions of the robot and its handling posture, and express its handling posture as a linear equation of y=kx+c, where k is a variable and c can be the value of a or b; Calculate the distance value d of all radar data points; Traversing the straight line equation y=kx+c corresponding to the disturbance coordinates (x±a, y, θ±b) of the vehicle posture after the disturbance is added, when the distance values ​​of all radar data points satisfy that d is greater than the half-width of the vehicle moving robot, the robot can pass through the chassis of the vehicle to be transported, enter the bottom of the transport vehicle, and perform transport operations on the transport vehicle.

7. A vehicle assessment system for robot vehicle handling, characterized in that: include: A data acquisition module, used to acquire the vehicle bottom lidar data of the vehicle to be transported through the lidar; A data segmentation module is used to segment and intercept the laser radar data of the bottom of the vehicle to be transported according to the distance between the laser radar and the ground, and obtain the corresponding wheel cross-section segmentation laser radar point cloud data; A coordinate calculation module, used to perform point cloud segmentation on the wheel cross-section segmentation laser radar point cloud data to obtain corresponding four wheel point cloud data, and determine corresponding wheel coordinate information according to the wheel point cloud data; Coordinate information processing, used to determine the corresponding wheelbase and vehicle posture according to the four wheel coordinate information of the vehicle to be transported; The data comparison module is used to determine whether the vehicle moving robot can pass through the vehicle to be moved according to the size of the vehicle moving robot, the wheelbase and the vehicle posture.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to claims 1 to 6 are implemented.

9. A computer device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to claims 1 to 6 are implemented.

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