Rubber-tired gantry crane positioning method and system based on single-line laser radar

Abstract

The present application relates to intelligent transportation, and discloses a rubber-tired gantry crane positioning method and system based on single-line laser radar. Said system comprises: a smart truck, a rubber-tired gantry crane, and single-line laser radars arranged on two sides of the smart truck. According to said method, by means of the single-line laser radars mounted on the two sides of the smart truck, front and rear beams of the rubber-tired gantry crane are scanned, corner points having the greatest curvatures on inner sides of the front and rear beams of the rubber-tired gantry crane are extracted by means of feature point extraction, and lastly, on the basis of a geometrical relationship, the relative position of the smart truck relative to the rubber-tired gantry crane is solved. Thus, the problems of high hardware costs and long computational time caused by the use of multi-line laser radar in the existing technology can be solved by the present application.

Description

A tire crane positioning method and system based on single-line laser radar Technical Field

[0001] This application belongs to intelligent transportation and involves a tire crane positioning method and system based on single-line laser radar. Background Art

[0002] In recent years, the development goals and implementation paths for digital transformation, intelligent upgrades, and integrated development of transportation have accelerated the development of smart transportation. New technologies are enabling ports to achieve reduced-manpower, automated, and intelligent transformation. Technological advances improve port efficiency, enhance safety, and reduce human involvement. These advancements not only enhance port competitiveness but also further improve productivity and promote efficient port operations. As ports transition to reduced-manpower operations, rubber-tired cranes (RTCs) play a crucial role in port operations. Smart trucks must be able to automatically and accurately dock within the center of the RTCs to facilitate their operation. However, smart trucks face limited global positioning accuracy under RTCs. Furthermore, obstruction by the RTCs and the surrounding container yards can easily block external signals, resulting in insufficient positioning accuracy for GPS systems under the RTCs. This makes it difficult for smart trucks to accurately dock under the RTCs. Therefore, a relatively accurate positioning method is needed under RTCs.

[0003] A Chinese invention patent with publication number CN111776948B, which is currently available, discloses a method and device for positioning a tire crane. This method involves installing a 40-line laser radar on an intelligent heavy-duty truck and fixing a reflector plate to the tire crane. By fixing the reflector plate to the tire crane and the 40-line laser radar on the intelligent heavy-duty truck, the method uses the 40-line laser radar to sense the intelligent heavy-duty truck's environment and extract point cloud data with a reflectivity greater than a set threshold. This method achieves precise positioning of the tire crane during automated port loading and unloading, meeting the positioning accuracy requirements of the tire crane and assisting the intelligent heavy-duty truck in completing automated port loading and unloading operations.

[0004] However, the above technology uses a 40-line laser radar, which has high hardware requirements and a large amount of computing power, resulting in the problem of excessively high usage costs.

[0005] Summary of the Invention

[0006] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not an extensive review, nor is it intended to identify key / critical elements or delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.

[0007] In order to solve the problems existing in the related art, the embodiments of the present disclosure provide a tire crane positioning method and system based on a single-line laser radar, which is used to solve the problems of high hardware cost and long calculation time caused by the use of multi-line laser radar in the existing technology.

[0008] In some embodiments, a tire crane positioning method based on a single-line laser radar is provided, which is applied to a tire crane positioning system. The tire crane positioning system includes: an intelligent truck, a tire crane, and single-line laser radars arranged on both sides of the intelligent truck. The method includes:

[0009] The smart truck moves to the docking area under the tire crane;

[0010] The single-line LiDAR scans the front and rear beams of the tire crane upwards to collect the original point cloud image;

[0011] The point cloud image is combined with the position of the single-line laser radar to convert it into a point cloud image in the coordinate system of the smart truck as the second point cloud image;

[0012] The second point cloud image is divided into four second point cloud images of left front, left rear, right front, and right rear, with the center of the smart truck as the center position;

[0013] Calculate the curvature of each point in the four second point cloud images of the left front, left back, right front, and right back;

[0014] Identify the points with the largest curvature on the four second point clouds respectively as the four corner points where the smart truck and the front and rear beams of the tire crane intersect in horizontal projection;

[0015] By using the coordinates of the four corner points of the second point cloud and the center position of the smart truck, the deviation between the smart truck and the tire crane is identified and adjusted.

[0016] In some embodiments, a tire crane positioning system based on a single-line laser radar is disclosed. The system includes: a smart truck, a tire crane, and single-line laser radars arranged on both sides of the smart truck.

[0017] Existing technologies tend to use multi-line laser radars to achieve the relative positioning of tire cranes and smart trucks. The current cost of multi-line laser radars is relatively higher. The use of multi-line laser radars results in a relatively large amount of data, which increases the time for calculating relative positioning. The present technical solution uses a single-line laser radar to effectively and quickly reduce costs and calculation time. The disclosed embodiment provides a tire crane positioning method and system based on a single-line laser radar. The system includes a smart truck, a tire crane, and single-line laser radars arranged on both sides of the smart truck. The method scans the front and rear beams of the tire crane by using single-line laser radars installed on both sides of the smart truck, extracts the corner points with the largest curvature on the inner side of the front and rear beams of the tire crane by feature point extraction, and finally solves the relative position of the smart truck relative to the tire crane based on the geometric relationship. Therefore, it can solve the problems of high hardware cost and long calculation time caused by the use of multi-line laser radars in the existing technology.

[0018] The above general description and the following description are exemplary and explanatory only and are not intended to limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] One or more embodiments are exemplarily described by the accompanying drawings. These exemplary descriptions and drawings do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements. The drawings do not constitute a scale limitation.

[0020] FIG1 is a schematic front view of a tire crane positioning system based on a single-line laser radar provided in an embodiment of the present disclosure;

[0021] FIG2 is a schematic top view of a tire crane positioning system based on a single-line laser radar provided in an embodiment of the present disclosure;

[0022] FIG3 is a flow chart of a tire crane positioning method based on a single-line laser radar provided in an embodiment of the present disclosure;

[0023] FIG4 is a schematic diagram of a point cloud P′ obtained by scanning a point cloud according to an embodiment of the present disclosure;

[0024] FIG5-1 is a schematic diagram of the right side of a tire crane and a smart truck provided by an embodiment of the present disclosure;

[0025] FIG5-2 is a schematic diagram of the left side of a tire crane and a smart truck provided by an embodiment of the present disclosure;

[0026] FIG6 is a schematic top view of a tire crane and a smart truck provided by an embodiment of the present disclosure;

[0027] FIG7 is a schematic diagram of calculating the relative positions of a tire crane and a smart truck provided by an embodiment of the present disclosure.

[0028] Reference numerals:

[0029] 1-Smart truck; 2-Tire crane; 3-Single-line laser radar; 4-Container; 21-Front and rear crossbeams; 211-Front crossbeam; 212-Rear crossbeam; 22-Tire crane slide rail; 23-Tire crane gripper. DETAILED DESCRIPTION

[0030] The prior art discloses a tire crane positioning method and device, which installs a 40-line laser radar on a smart heavy truck, and fixes a reflector on the tire crane. This method uses a 40-line laser radar to sense the environment of the smart heavy truck by fixing the reflector on the tire crane and the 40-line laser radar on the smart heavy truck, and extracts point cloud data with a reflectivity greater than a set threshold. This achieves precise positioning of the tire crane during the automated loading and unloading of containers at the port, so that it meets the positioning accuracy requirements of the tire crane, thereby assisting the smart heavy truck in completing the automated loading and unloading of containers at the port. Existing technology tends to use multi-line laser radars to achieve relative positioning between the tire crane and the smart truck. The current cost of multi-line laser radars is relatively higher. The use of multi-line laser radars results in a relatively large amount of data, which increases the time for calculating relative positioning.

[0031] To address the high hardware costs and long computation times associated with the use of multi-line LiDARs in existing technologies, Figures 1 and 2 show front and top views of a single-line LiDAR-based tire crane positioning system. The system comprises an intelligent truck 1, a tire crane 2, and single-line LiDARs 3 positioned on either side of the truck. The tire crane 2 grasps a container 4 using its gripper 23 and moves the container 4 using its slide rails 22.

[0032] As shown in FIG3 , the embodiment of the present disclosure provides a positioning method for a tire crane 2 based on a single-line laser radar 3 , including:

[0033] S100: The smart truck 1 runs to the operation docking area below the tire crane 2.

[0034] It should be understood that the intelligent truck 1, based on its autonomous driving system, first performs docking at an initial position. It should be noted that the accuracy of the initial docking is insufficient to achieve the desired precise docking of the container 4. Therefore, precise positioning and docking are required in subsequent steps.

[0035] In step S200 , the single-line laser radar 3 scans the front and rear beams 21 of the tire crane 2 upwards to collect an original point cloud image.

[0036] It should be understood that the single-line laser radar 3 is located on both sides of the smart truck 1 and scans the front and rear beams 21 of the tire crane 2 above it vertically upward.

[0037] S300: The point cloud image is combined with the position of the single-line laser radar 3 to convert the point cloud image in the coordinate system of the smart truck 1 into a second point cloud image.

[0038] The results of a single scan by the single-line LiDAR 3 on both sides of smart truck 1 are converted into a point cloud P in the coordinate system of the smart truck's center. The initial scan results of the single-line LiDAR 3 on both sides are converted to the coordinate system of the smart truck's center using the external parameters of the single-line LiDAR 3. The x-axis is directly in front of smart truck 1, the y-axis is directly to the left, and the z-axis is vertically upward.

[0039] Furthermore, the second point cloud image is filtered out of useless point clouds. Specifically, the maximum value z_max and the minimum value z_min required for actual measurement of the z-axis are filtered out by the straight-through filter to obtain the point cloud P'.

[0040] See Figure 4, which is a schematic diagram of a point cloud P' obtained by scanning a point cloud in an embodiment of the present disclosure. max Indicates the maximum distance that a single-line laser radar can reach from the front and rear beams, Z min Indicates the shortest distance between the single-line laser radar and the front and rear beams. min Misalignment means that the laser radar distance measurement has a certain amount of noise, and it needs to be lower than the bottom edge of the beam to ensure that the effective data is filtered out. max Alignment for efficient data filtering.

[0041] S400: Divide the second point cloud map into four second point cloud maps of left front, left rear, right front, and right rear, with the center of the smart truck as the center position and the corresponding horizontal projection.

[0042] In the coordinate system of the center of the smart truck, the second point cloud image is cut into four parts: left front, left rear, right front, and right rear, with x and y as boundaries.

[0043] S500: Calculate the curvature of each point in the four second point cloud images of the left front, left rear, right front, and right rear.

[0044] The filtered point cloud P' is divided into four points of the second point cloud map: left front, left back, right front, and right back, which are P' lf , P' lr , P' rf , P' rr Among them, P' lf Represents the second point cloud point on the left front, P' lr Represents the point of the second point cloud from the left rear, P' rf Represents the point of the second point cloud in the right front, P' rrIndicates the point of the second point cloud in the right rear. See Figures 5-1 and 5-2, which are respectively the right and left schematic diagrams of the tire crane 2 and the smart truck 1 in the embodiment of the present disclosure. In order to obtain the points on the lower edge of the beam above the tire crane, these points are the points with large curvature. The curvature of the continuous discrete point cloud is solved using this formula

[0045] Calculate the curvature c of each point on each second point cloud map, and the curvature c of the i-th point i is defined as follows:

[0046] Among them, c i Represents the curvature of the i-th point in the ordered point cloud, p i Represents the three-dimensional space coordinate system vector of the i-th point in the ordered point cloud, p i+n The vector representing the three-dimensional space coordinate system of the i+nth point in the ordered point cloud, p i-n The vector representing the three-dimensional space coordinate system of the in-th point in the ordered point cloud, ||p i || represents the modulus operation of a three-dimensional vector.

[0047] S600: Identify the points with the largest curvature on the four second point clouds respectively as the four corner points where the smart truck 1 and the front and rear beams 21 of the tire crane 2 intersect in the horizontal projection.

[0048] Get the minimum curvature value c_min required when obtaining the corner point; filter the curvature c of each point and filter out the points less than c_min; select the points with the largest curvature by sorting the curvature, which are p' lf =x' lf ,y' lf ,z' lf ),p' lr =(x' lr ,y' lr ,z' lr ), p' rf =(x' rf ,y' rf ,z' rf ), p' rr =(x' rr ,y' rr ,z' rr ). Among them, x' lf ,y' lf ,z' lf ) represents the coordinate value of the point with the largest curvature in the second point cloud from the left front; (x' lr ,y' lr ,z' lr ) represents the coordinate value of the point with the largest curvature in the second point cloud on the left rear; (x' rf ,y'rf ,z' rf ) represents the coordinate value of the point with the largest curvature in the second point cloud on the right front; (x' rf ,y' rf ,z' rf ) represents the coordinate value of the point with the largest curvature in the second point cloud image on the right rear.

[0049] The minimum curvature requirement c_min at the corner point can be obtained from practical measurement experience and is used to exclude unreasonable points.

[0050] S700: Identify the deviation between the smart truck 1 and the tire crane 2 by using the coordinates of the four corner points in the second point cloud and the center position of the smart truck 1, and make adjustments.

[0051] Selecting any three of the four points with the greatest curvature can determine the lower plane G of the Tire Crane's beam. A greater curvature indicates a greater change before and after that point. In the Tire Crane's operating environment, extracting the point with the greatest curvature ensures that it lies on the lower edge of the beam above the Tire Crane, which in turn lies on the lower plane of the beam.

[0052] Through point p' lf and point p' rf The straight line L1 of the front cross beam 211 of the tire crane 2 can be obtained by solving the problem, passing through the point p' lr and point p' rr Solve for the line L2 of the rear crossbeam 212. The parametric representation of the line equation in three-dimensional geometric space is as follows: select a starting point, and then use the direction vector of the line and the parameter t to form a representation of the line in three-dimensional space.

[0053] The straight line L1 is represented as

[0054] The straight line L2 is expressed as

[0055] Among them, x 01 Indicates the x-axis value of a point on the line L1 in the three-dimensional space coordinates, y 01 Indicates the value of the y-axis of a point on the straight line L1 in the three-dimensional space coordinates, 01 Represents the z-axis value of a point on the straight line L1 in the three-dimensional space coordinates, m1 represents the x-axis value of the direction vector of the straight line L1 in the three-dimensional space coordinates, n1 represents the y-axis value of the direction vector of the straight line L1 in the three-dimensional space coordinates, p1 represents the z-axis value of the direction vector of the straight line L1 in the three-dimensional space coordinates, and t1 is a parameter representing the straight line L1;

[0056] x 02 Indicates the x-axis value of a point on the line L2 in the three-dimensional space coordinates, y 02Indicates the value of the y-axis of a point on the straight line L2 in the three-dimensional space coordinates, z 02 It represents the z-axis value of a point on the straight line L2 in the three-dimensional space coordinates, m2 represents the x-axis value of the direction vector of the straight line L2 in the three-dimensional space coordinates, n2 represents the y-axis value of the direction vector of the straight line L2 in the three-dimensional space coordinates, p2 represents the z-axis value of the direction vector of the straight line L2 in the three-dimensional space coordinates, and t2 is a parameter representing the straight line L2.

[0057] Refer to Figure 6, which is a top view of a tire crane 2 and a smart truck 1 in an embodiment of the present disclosure.

[0058] Project the center coordinate point O of the smart truck 1 vertically onto the plane G, and we get O'=(x' o ,y' o ,z' o ), then solve the Euclidean distance d1 between O' and L1 according to the distance formula of three-dimensional points and lines;

[0059] Among them, ||(m1, n1, p1)|| represents the modular operation of this three-dimensional vector, m1 represents the value of the direction vector of the straight line L1 on the x-axis in the three-dimensional space coordinates, n1 represents the value of the direction vector of the straight line L1 on the y-axis in the three-dimensional space coordinates, and p1 represents the value of the direction vector of the straight line L1 on the z-axis in the three-dimensional space coordinates; ||(x' o -x 02 ,y' o -y 02 ,z' o -z 02 )×(m2, n2, p2)|| represents the vector (x' o -x 01 ,y' o -y 01 ,z' o -z 01 ) and the vector (m1, n1, p1) modulo operation, x' o Indicates the value of the x-axis of the three-dimensional space coordinate system of point O', y' o Indicates the value of the y-axis of the three-dimensional space coordinate system of point O', z' o Indicates the value of the z-axis of the three-dimensional space coordinate system of point O'. 01 Indicates the x-axis value of a point on the line L1 in the three-dimensional space coordinates, y 01 Indicates the value of the y-axis of a point on the straight line L1 in the three-dimensional space coordinates, 01 Indicates the z-axis value of a point on line L1 in three-dimensional space coordinates.

[0060] Similarly, according to the distance between the three-dimensional space system point and the straight line, solve the Euclidean distance d2 between O' and L2;

[0061] Among them, ||(m2, n2, p2)|| represents the modular operation of this three-dimensional vector, m2 represents the value of the direction vector of the straight line L2 on the x-axis in the three-dimensional space coordinates, n2 represents the value of the direction vector of the straight line L2 on the y-axis in the three-dimensional space coordinates, p2 represents the value of the direction vector of the straight line L2 on the z-axis in the three-dimensional space coordinates, ||(x' o -x 02 ,y' o -y 02 ,z' o -z 02 )×(m2,n2,p2)||

[0062] Represents the vector (x' o -x 02 ,y' o -y 02 ,z' o -z 02 ) and the vector (m2, n2, p2) modulo operation, x' o Indicates the value of the x-axis of the three-dimensional space coordinate system of point O', y' o Indicates the value of the y-axis of the three-dimensional space coordinate system of point O', z' o Indicates the value of the z-axis of the three-dimensional space coordinate system of point O'. 02 Indicates the x-axis value of a point on the line L2 in the three-dimensional space coordinates, y 02 Indicates the value of the y-axis of a point on the straight line L2 in the three-dimensional space coordinates, z 02 Indicates the z-axis value of a point on line L2 in three-dimensional space coordinates.

[0063] The distance between the center of the smart truck and the straight line L1 below the front crossbeam 211 of the tire crane 2 is d1, and the distance between the center of the smart truck and the straight line L2 below the rear crossbeam 212 of the tire crane 2 is d2. The position d of the center of the smart truck relative to the center line of the tire crane 2 is obtained;

[0064] Vector p' lf p' rf The heading angle relative to the center coordinate system of the smart truck is heading1, and the vector p' lr p' rr The heading angle relative to the center coordinate system of the smart truck is heading2.

[0065] The heading of the intelligent truck center coordinate system relative to the center line L of the tire crane 2 can be solved, and the distance D from the front crossbeam 211 to the rear crossbeam 212 of the tire crane 2 can be measured in advance. sFinally, the heading of the center coordinate system of the smart truck relative to the center line of the tire crane 2 ensures that the control of the smart truck 1 under the tire crane 2 is perpendicular to the tire beam, and the distance from the front beam 211 to the rear beam 212 of the tire crane 2 is D s It is used to accurately park the smart truck 1 below the center line of the tire crane 2.

[0066] 7 , which is a schematic diagram of calculating the relative positions of a tire crane 2 and a smart truck 1 in an embodiment of the present disclosure.

[0067] The position of the center of the smart truck relative to the center line of the tire crane 2 is calculated as follows

[0068] Vector p' lf p' rf The heading angle relative to the center coordinate system of the smart truck is calculated as follows:

[0069] heading1=atan2(y′ rf -y′ lf ,x′ rf -x′ lf );

[0070] heading1 is represented by the vector p' lf p' rf The heading angle relative to the center coordinate system of the smart truck, atan2 represents an inverse tangent function in mathematics, y' rf Represents point p' rf The value of a y-axis in a three-dimensional space coordinate system, y' lf Represents point p' lf The value of a y-axis in a three-dimensional space coordinate system, x' rf Represents point p' rf The value of an x-axis in a three-dimensional space coordinate system, x' lf Represents point p' lf The value of an x-axis in a three-dimensional space coordinate system;

[0071] Vector p' lr p' rr The heading angle relative to the intelligent truck center coordinate system is calculated as follows: heading2=atan2(y' rr -y' lr ,x' rr -x' lr );

[0072] heading2 is represented by the vector p' lr p' rr The heading angle relative to the center coordinate system of the smart truck, atan2 represents an inverse tangent function in mathematics, y' rrRepresents point p' rr The value of a y-axis in a three-dimensional space coordinate system, y' lr Represents point p' lr The value of a y-axis in a three-dimensional space coordinate system, x' rr Represents point p' rr The value of an x-axis in a three-dimensional space coordinate system, x' lr Represents point p' lr The value of an x-axis in a three-dimensional space coordinate system;

[0073] The heading angle of the intelligent truck center coordinate system relative to the center line of the tire crane 2 is calculated as follows:

[0074] Where, heading is the heading angle of the intelligent truck center coordinate system relative to the tire crane center line, and pi is pi.

[0075] Then, based on the distance deviation and heading angle, the precise position of smart truck 1 is adjusted so that smart truck 1 and tire crane 2 can accurately dock container 4. Specifically, control is implemented to ultimately make the distance deviation zero, and control the vehicle's heading angle to match the heading angle of the tire crane.

[0076] An optimized embodiment may be that the tire crane 2 has a positioning module. The method further includes:

[0077] S800 , compensating the deviation between the smart truck 1 and the tire crane 2 into the smart truck position in the global positioning, and obtaining the corrected smart truck position in the global positioning, where the global positioning comes from the positioning module of the tire crane 2 .

[0078] Specifically, the position d of the center of the smart truck relative to the center straight line of the tire crane 2, and the heading of the center coordinate system of the smart truck relative to the center line of the tire crane 2. Since the signal of the smart truck 1 is easily blocked when entering the yard area, it is easy to cause the offset of the global fusion positioning module and the positioning accuracy is reduced. The tire crane 2 itself is equipped with a positioning system module. Since the position of the tire crane 2 is relatively high, there will be no signal blocking problem, so the positioning module of the tire crane 2 has a relatively high accuracy, so that the smart truck 1 can be sent in real time through the local area network system of the tire crane 2.

[0079] Get the coordinates of the center of the tire crane 2 in the global coordinate system (x L ,y L ,heading L), combined with the known position d of the center of the smart truck relative to the center line of the tire crane 2 and the heading relative to the center line, this observation is updated using the update step of the global fusion positioning module to ensure the accuracy of the global fusion positioning system in the yard area. The coordinates of the smart truck 1 obtained by fusion positioning in the global coordinate system are expressed as (x Fuse ,y Fuse ,heading Fuse ), obtain the position of the smart truck 1 relative to the tire crane 2;

[0080] The observation equation in the Kalman filter is as follows:

[0081] Among them, heading L Indicates the heading angle of the center coordinate of the tire crane in the global coordinate system. Heading is the heading angle of the intelligent truck center coordinate system relative to the tire crane center line. Fuse Indicates the x-axis value of the smart truck coordinate obtained by fusion positioning in the global coordinate system, y Fuse Indicates the y-axis value of the smart truck coordinate obtained by fusion positioning in the global coordinate system, heading Fuse Represents the heading angle of the smart truck coordinates obtained by fusion positioning in the global coordinate system.

[0082] In this disclosed embodiment, single-line laser radars 3 mounted on either side of the smart truck 1 scan the front and rear beams 21 of the tire crane 2. Feature point extraction is used to identify the corner with the maximum curvature on the inner side of the tire crane's front and rear beams 21. Finally, the relative position of the smart truck 1 relative to the tire crane 2 is determined based on the geometric relationship. This solves the high hardware cost and long computation time issues associated with using multi-line laser radars in the prior art.

Claims

1. A tire crane positioning method based on a single-line laser radar, characterized in that: Applied to a tire crane positioning system, the tire crane positioning system comprises: an intelligent truck, a tire crane and single-line laser radars arranged on both sides of the intelligent truck, the method comprises: The smart truck runs to the working docking area under the tire crane; The single-line laser radar scans the front and rear beams of the tire crane upwards to collect the original point cloud image; The point cloud image is combined with the position of the single-line laser radar to convert it into a point cloud image in the coordinate system of the smart truck as the second point cloud image; The second point cloud map is divided into four second point cloud maps of left front, left rear, right front and right rear by taking the center of the smart truck as the center position and corresponding horizontal projection; Calculate the curvature of each point in the four second point cloud images of left front, left back, right front and right back; The points with the largest curvature on the four second point clouds are respectively identified as the four corner points where the front and rear beams of the smart truck and the tire crane intersect in the horizontal projection; By using the coordinates of the four corner points of the second point cloud and the center position of the smart truck, the deviation between the smart truck and the tire crane is identified and adjusted.

2. The method according to claim 1, characterized in that The curvature of each point in the four second point cloud images of left front, left back, right front and right back is calculated, including: Suppose the points of the four second point clouds at the left front, left back, right front, and right back are P′ lf , P′ lr , P′ rf , P′ rr , where P′ lf Represents the point of the second point cloud from the left front, P′ lr Represents the point of the second point cloud image on the left, P′ rf Represents the point of the second point cloud in the right front, P′ rr Represents the point of the second point cloud at the right rear; Calculate the curvature c of each point for each second point cloud image. The curvature of the i-th point is defined as follows: Among them, c i represents the curvature of the i-th point in the ordered point cloud, p i Represents the three-dimensional space coordinate system vector of the i-th point in the ordered point cloud, p i+n The vector representing the three-dimensional space coordinate system of the i+nth point in the ordered point cloud, p i-n The vector representing the three-dimensional space coordinate system of the in-th point in the ordered point cloud, ||p i || represents the modulus operation of a three-dimensional vector.

3. The method according to claim 2, characterized in that The points with the largest curvature on the four second point clouds are identified as the four corner points where the front and rear beams of the smart truck and the tire crane intersect in the horizontal projection, including: The minimum curvature required when obtaining the corner point c_min; Screen the curvature c of each point and filter out points that are less than c_min; By sorting the curvature, we select the points with the largest curvature, which are p′ lf =(x′ lf ,y′ lf ,z′ lf ), p′ lr =(x′ lr ,y′ lr ,z′ lr ),p′ rf =(x′ rf ,y′ rf ,z′ rf ),p′ rr =(x′ rr ,y′ rr ,z′ rr ); Among them, (x′ lf ,y′ lf ,z′ lf ) represents the coordinate value of the point with the largest curvature in the second point cloud image on the left front; (x′ lr ,y′ lr ,z′ lr ) represents the coordinate value of the point with the largest curvature in the second point cloud image on the left rear; (x′ rf ,y′ rf ,z′ rf ) represents the coordinate value of the point with the largest curvature in the second point cloud image on the right front; (x′ rf ,y′ rf ,z′ rf ) represents the coordinate value of the point with the largest curvature in the second point cloud image on the right rear.

4. The method according to claim 3, characterized in that By using the coordinates of the four corner points of the second point cloud and the center position of the smart truck, the deviation between the smart truck and the tire crane is identified, including: Randomly selecting three of the four points with the largest curvature can solve the plane G under the tire crane beam; Through the point p′ lf and point p′ rf The straight line L1 of the front crossbeam of the tire crane can be obtained by solving the problem, passing through the point p′ lr and point p′ rr Solve for the rear beam straight line L2; The straight line L1 is expressed as The straight line L2 is expressed as Among them, x 01 Represents the x-axis value of a point on the straight line L1 in the three-dimensional space coordinates, y 01 Represents the value of the y-axis of a point on the straight line L1 in the three-dimensional space coordinates, z 01 represents the z-axis value of a point on the line L1 in the three-dimensional space coordinates, and m1 represents the direction vector of the line L1 in the three-dimensional space coordinates. The x-axis value in the mark, n1 represents the y-axis value of the direction vector of the straight line L1 in the three-dimensional space coordinates, p1 represents the z-axis value of the direction vector of the straight line L1 in the three-dimensional space coordinates, and t1 belongs to the parameter represented by the straight line L1; x 02 Represents the x-axis value of a point on the line L2 in the three-dimensional space coordinates, y 02 represents the value of the y-axis of a point on the line L2 in the three-dimensional space coordinates, 02 represents the z-axis value of a point on the straight line L2 in the three-dimensional space coordinates, m2 represents the x-axis value of the direction vector of the straight line L2 in the three-dimensional space coordinates, n2 represents the y-axis value of the direction vector of the straight line L2 in the three-dimensional space coordinates, p2 represents the z-axis value of the direction vector of the straight line L2 in the three-dimensional space coordinates, and t2 is a parameter representing the straight line L2; Project the center coordinate point O of the smart truck vertically onto plane G, and we get O′=(x′ o ,y′ o ,z′ o ), and then solve the distance formula between O′ and L1 and the Euclidean distance d1 according to the distance formula between points and lines in three-dimensional space; Among them, ||(m1, n1, p1)|| represents the modular operation of this three-dimensional vector, Where m1 represents the value of the direction vector of the straight line L1 on the x-axis in the three-dimensional space coordinates. n1 represents the value of the direction vector of the straight line L1 on the y-axis in the three-dimensional space coordinates. p1 represents the value of the direction vector of the straight line L1 on the z-axis in the three-dimensional space coordinates; ||(x′ o -x 02 ,y′ o -y 02 ,from' o -z 02 )×(m2,n2,p2)|| Represents the vector (x′ o -x 01 ,y′ o -y 01 ,z′ o -z 01 ) and the vector (m1, n1, p1), x′ o Represents the value of the x-axis of the three-dimensional space coordinate system of point O′, y′ o Represents the value of the y-axis of the three-dimensional space coordinate system of point O′, z′ o Represents the value of the z-axis of the three-dimensional space coordinate system of point O′, x 01 Represents the x-axis value of a point on the straight line L1 in the three-dimensional space coordinates, y 01 Represents the value of the y-axis of a point on the straight line L1 in the three-dimensional space coordinates, z 01 Represents the value of the z-axis of a point on the straight line L1 in the three-dimensional space coordinates; Similarly, O′ and L2 and the Euclidean distance d2 are solved according to the distance between the three-dimensional space system point and the straight line; Among them, ||(m2, n2, p2)|| represents the modular operation of this three-dimensional vector, m2 represents the value of the direction vector of the straight line L2 on the x-axis in the three-dimensional space coordinates, n2 represents the value of the direction vector of the straight line L2 on the y-axis in the three-dimensional space coordinates, and p2 represents the value of the direction vector of the straight line L2 on the z-axis in the three-dimensional space coordinates. ||(x′ o -x 02 ,y′ o -y 02 ,from' o -z 02 )×(m2,n2,p2)|| Represents the vector (x′ o -x 02 ,y′ o -y 02 ,z′ o -z 02 ) and the vector (m2, n2, p2), x′ o Represents the value of the x-axis of the three-dimensional space coordinate system of point O′, y′ o Represents the value of the y-axis of the three-dimensional space coordinate system of point O′, z′ o Represents the value of the z-axis of the three-dimensional space coordinate system of point O′, x 02 Represents the x-axis value of a point on the line L2 in the three-dimensional space coordinates, y 02 represents the value of the y-axis of a point on the line L2 in the three-dimensional space coordinates, 02 Represents the z-axis value of a point on the line L2 in the three-dimensional space coordinates; The distance between the center of the smart truck and the straight line L1 below the front beam of the tire crane is d1, and the distance between the center of the smart truck and the straight line L2 below the rear beam of the tire crane is d2, and the position d of the center of the smart truck relative to the center straight line of the tire crane is obtained; Vector p′ lf p′ rf The heading angle relative to the center coordinate system of the smart truck is heading1, and the vector p′ lr p′ rr The heading angle relative to the center coordinate system of the smart truck is heading2, and the heading of the center coordinate system of the smart truck relative to the center line L of the tire crane is solved; According to the distance from the front beam to the rear beam of the tire crane is D s ; The position of the center of the smart truck relative to the center line of the tire crane is calculated as follows Vector p′ lf p′ rf The heading angle relative to the smart truck center coordinate system is calculated as follows: heading1=atan2(y′ rf -y′ lf ,x′ rf -x′ lf ); heading1 is represented by the vector p′ lf p′ rf The heading angle relative to the center coordinate system of the smart truck, atan2 is a mathematical inverse tangent function, y′ rf Represents point p′ rf The value of a y-axis in a three-dimensional space coordinate system, y′ lf Represents point p′ lf The value of a y-axis in a three-dimensional space coordinate system, x′ rf Represents point p′ rf The value of an x-axis in a three-dimensional space coordinate system, x′ lf Represents point p′ lf The value of an x-axis of a three-dimensional space coordinate system; Vector p′ lr p′ rr The heading angle relative to the smart truck center coordinate system is calculated as follows: heading2=atan2(y′ rr -y′ lr ,x′ rr -x′ lr ); heading2 is represented by the vector p′ lr p′ rr The heading angle relative to the center coordinate system of the smart truck, atan2 is a mathematical inverse tangent function, y′ rr Represents point p′ rr The value of a y-axis in a three-dimensional space coordinate system, y′ lr Represents point p′ lr The value of a y-axis in a three-dimensional space coordinate system, x′ rr Represents point p′ rr The value of an x-axis in a three-dimensional space coordinate system, x′ lr Represents point p′ lr The value of an x-axis of a three-dimensional space coordinate system; The heading angle of the intelligent truck center coordinate system relative to the tire crane center line is calculated as follows: Among them, heading is the heading angle of the intelligent truck center coordinate system relative to the center line of the tire crane, and pi is pi.

5. The method according to claim 4, characterized in that The tire crane has a positioning module, and the method further comprises: The deviation between the smart truck and the tire crane is compensated into the position of the smart truck in the global positioning, and the position of the smart truck in the global positioning after calibration is obtained, and the global positioning comes from the positioning module of the tire crane.

6. The method according to claim 5, characterized in that The deviation between the smart truck and the tire crane is compensated into the smart truck position in the global positioning, and the smart truck position in the global positioning after calibration is obtained, including: Get the coordinates of the center of the tire crane in the global coordinate system (x L ,y L ,heading L ), combined with the known position d of the center of the smart truck relative to the center line of the tire crane and the heading relative to the center line, combined with the use of Kalman filtering in the process, the coordinates of the smart truck obtained by fusion positioning are expressed in the global coordinate system as (x Fuse ,y Fuse ,heading Fuse ), and obtain the position of the smart truck relative to the tire crane; The observation equation in the Kalman filter is as follows: Among them, heading L Indicates the heading angle of the coordinates of the center of the tire crane in the global coordinate system. Heading is the heading angle of the intelligent truck center coordinate system relative to the center line of the tire crane. Fuse Indicates the x-axis value of the smart truck coordinates obtained by fusion positioning in the global coordinate system, Fuse Indicates the y-axis value of the smart truck coordinates obtained by fusion positioning in the global coordinate system, heading Fuse Represents the heading angle of the smart truck coordinates obtained by fusion positioning in the global coordinate system.

7. The method according to claim 1, characterized in that Before the smart truck runs to the working docking area under the tire crane, it also includes: Based on the collected container yard operation map and the positioning module of the smart truck, the smart truck plans the implementation trajectory.

8. The method according to claim 1, characterized in that: The second point cloud image is divided into four blocks of left front, left rear, right front and right rear by taking the center of the smart truck as the center position. Before the second point cloud image, it also includes: The second point cloud image is filtered out with a filter to remove useless point clouds.

9. A tire crane positioning system based on a single-line laser radar, characterized in that: The system includes: an intelligent truck, a tire crane, and single-line laser radars arranged on both sides of the intelligent truck.

10. The tire crane positioning system according to claim 9, characterized in that: The tire crane comprises a positioning module.

Images