AGV positioning and docking method
By using a combination of laser radar and reflector on the AGV car, combined with coordinate system conversion and evaluation function matching, the precise positioning and scanning code docking of the AGV car is achieved under the machine platform, solving the problems of navigation deviation and docking failure in the existing technology, and improving the accuracy and reliability of material loading, unloading and handling.
Patent Information
- Application Number
- CN202411957136.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-29
- Publication Date
- 2025-04-04
- Estimated Expiration
- 2044-12-29
AI Technical Summary
When existing AGV cars are positioned and connected under the machine, it is difficult to achieve accurate driving and scanning code docking, especially when the machine displacement or reflector data uncertainty, resulting in navigation deviation and docking failure.
By setting up a reflector in front of the machine and scanning point cloud data using lidar, combining coordinate system conversion and evaluation function matching, the position and path of the AGV car is determined to ensure that the car is driving at the center of the reflector, and the precise docking of the bottom of the machine is achieved through the distance of the center point of the QR code.
It realizes the precise positioning and scanning code connection of the AGV car under the machine, improves the accuracy and reliability of material loading and unloading and handling, and adapts to the displacement of the machine.
Smart Images

Figure CN119759031A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the technical field of robot navigation, and in particular to an AGV trolley positioning and docking method. Background Art
[0002] In recent years, with the continuous improvement of production technology, most modern intelligent manufacturing workshops are equipped with intelligent mobile robots, and AGV carts are one of the intelligent mobile robots. They locate and navigate to dock with other logistics equipment to achieve loading and unloading and transportation of materials. In this process, compared with the traditional rail navigation docking method, the positioning and navigation technology based on laser radar is the key technology for AGV carts to navigate and complete docking in indoor workshops. The navigation method based on laser radar has high accuracy.
[0003] For example, the Chinese patent application number is 201710571639.9, and the publication date is September 8, 2017. It discloses a laser positioning and navigation method based on double reflectors. The minimum requirement of the method is to detect two reflectors, but in actual application, multiple reflectors may be detected at the same time. By designing data fusion processing, the complex domain information of the reflectors can be maximized, thereby further improving the accuracy.
[0004] In the workshop, when the AGV needs to be controlled to transport materials under the machine, the AGV needs to accurately find the positioning point before it can drive to the bottom of the machine to dock. However, the double reflectors in the above literature only allow the AGV to drive in front of the reflector of the machine. At the same time, if the AGV is close to the reflector in front of the machine, the data of the scanned reflector may be uncertain and deviated during the matching process of the reflector. However, if a QR code is used for navigation under the machine, the QR code needs to be preset at the bottom of the machine. If the machine is displaced during the movement of the AGV, the movement to the position without the QR code will make it impossible to navigate the bottom of the machine after the movement, thereby failing to ensure that the AGV drives accurately to the bottom of the machine to scan the code for docking, and then complete the loading and unloading and transportation of materials. Summary of the invention
[0005] The purpose of the present invention is to provide an AGV trolley positioning and docking method, so that the AGV trolley can accurately drive to the bottom of the machine platform to scan the code and complete the docking, and the method is simple and reliable.
[0006] In order to achieve the above-mentioned purpose, the present invention provides an AGV trolley positioning and docking method, wherein reflective plates are provided on both sides in front of the machine platform, the length of the machine platform is preset to be c, the width of the machine platform is preset to be d, and the QR code is set at the center position of the bottom of the machine platform. The distance of the center point of the QR code is directly determined by different coordinate system conversions to achieve positioning, and the trolley is driven from the middle position of the reflective plate into the bottom of the machine platform to scan the code for docking. The following steps are involved: S1, control the AGV to enter the reflector scanning area in front of the machine and switch to the reflector positioning mode, and then start matching the reflector contour; S1.1, Scan the point cloud data in the reflector area by the laser radar installed on the AGV, preset the point cloud intensity threshold T, weighting coefficients α, β, γ, S1.2, collect the scanned point cloud data, and then filter the point cloud data according to the preset intensity threshold T, S1.3, determine the error between the contour length of the screened point cloud data and the length of the reflector, determine the center spacing error between the screened point cloud data and the reflector, determine the relative intensity error between the screened point cloud data and the reflector, and use the evaluation function cost to determine whether the reflector contour matches; the evaluation function cost is a weighted coefficient and a weighted sum of the length error, the center spacing error, and the relative intensity error; S2. Obtain the pose matrix of the reflector in the laser radar coordinate system through the coordinates of the point cloud data , then according to the transformation matrix T of the laser radar in the odometer coordinate system b Get the pose matrix T of the reflector in the odometer coordinate system g , according to the transformation matrix T of the origin of the odometer coordinate system in the AGV vehicle coordinate system r Get the pose matrix T of the reflector in the AGV coordinate system L ; S3, according to the pose matrix T of the reflector in the AGV car coordinate system L Determine whether the AGV is on the straight path where the center position between the reflectors is located. If there is a deviation error, correct the deviation error to make the AGV return to the straight path where the center position between the reflectors is located; S4. Taking the center of the reflector on one side of the machine as the origin, establish a reflector coordinate system, and then determine the position coordinates of the center point of the QR code in the reflector coordinate system as (x1, y1, z1) according to the length and width of the machine. S5, preset the transformation matrix between the reflector coordinate system and the odometer coordinate system as T1, through the transformation matrix T1, the position matrix T3 of the center point of the two-dimensional code in the odometer coordinate system can be obtained, the transformation matrix between the AGV trolley coordinate system and the odometer coordinate system is preset as T2, and the position matrix T3 is combined with the transformation matrix T2 to obtain the position matrix T4 of the center point of the two-dimensional code in the AGV trolley coordinate system; S6. Calculate the straight-line distance between the center point of the QR code and the AGV through the position matrix T4, and then control the AGV to drive straight to the scanning area at the center of the bottom of the machine to achieve scanning docking.
[0007] With the above settings, the laser radar is used to scan the point cloud data in the scanning area in front of the machine, and the point cloud intensity threshold T is preset. This makes it easier to compare the preset point cloud intensity threshold T with the intensity of the scanned point cloud data, thereby screening out the point cloud data that matches the reflector, eliminating other interference factors and improving accuracy; then, the coordinates of the screened point cloud data (lx i ,ly i ) to obtain the pose matrix of the reflector in the laser radar coordinate system , and then according to the transformation matrix T of the laser radar in the odometer coordinate system b , so that the pose matrix T of the reflector in the odometer coordinate system can be obtained g At the same time, the transformation matrix T of the origin of the odometer coordinate system in the AGV vehicle coordinate system r , so that the pose matrix T of the reflector in the AGV coordinate system can be obtained L , so that the reflector can be used in the AGV car coordinate system through the pose matrix T L Determine whether the AGV is on the straight path where the center position between the reflectors is located, and ensure that the AGV is on the straight path where the center position between the reflectors is located; by setting the transformation matrix between the reflector coordinate system and the odometer coordinate system to T1, and setting the transformation matrix between the AGV coordinate system and the odometer coordinate system to T2, the position matrix T3 of the center point of the QR code in the odometer coordinate system can be obtained through the transformation matrix T1, so that the position matrix T3 and the transformation matrix T2 can be combined to calculate the position matrix T4 of the center point of the QR code in the AGV coordinate system, and then calculate the straight-line distance between the center point of the QR code and the AGV, and then control the AGV to drive straight to the scanning area at the center position of the bottom of the machine to realize scanning docking, and realize the loading and unloading and handling of materials. For example, during the movement of the AGV, the machine moves, and the center of the QR code at the bottom is the center of the AGV, and then the center of the AGV is mapped to the reflector coordinate system, and then the moving path of the AGV is obtained after matrix transformation, so that the AGV moves to the machine position for docking.
[0008] Furthermore, the err_length function is used to calculate the error between the contour length of the filtered point cloud data and the length of the reflector, the err_dist function is used to calculate the center distance error between the filtered point cloud data and the reflector, the cost_intensity function is used to calculate the relative intensity error between the filtered point cloud data and the reflector, and the evaluation function cost is used to determine whether the reflector contour matches.
[0009] With the above settings, the length error, center distance error, and relative intensity error between the filtered point cloud data and the reflector are calculated through the err_length function, err_dist function, and cost_intensity function, respectively. Then, the evaluation function cost can be obtained and used to determine whether the reflector contour matches. In this way, the AGV can complete the contour matching of the scanned reflector.
[0010] Furthermore, the step S1.2 also includes: The intensity threshold T0 of the scanned point cloud data is compared with the preset intensity threshold T. If T0 is within the range of [0.6*T, 0.7*T], it is judged as the point cloud data of the reflector; otherwise, it is judged as other interfering point cloud data.
[0011] The above settings can filter out the point cloud data that matches the reflector from all the scanned point cloud data.
[0012] Furthermore, the step S1.3 also includes: The formula of the evaluation function cost is as follows: cost=α* err_length+ β*err_dist+ γ*cost_intensity(1).
[0013] The above settings make it easy to determine whether the reflector profile matches through the evaluation function cost.
[0014] Furthermore, the step S2 also includes calculating the coordinates of the filtered point cloud data (lx i ,ly i ), the specific steps are as follows: S2.1. Obtain the distance l between the laser radar and the reflector and the scanning angle z from the laser radar scan. S2.2, then use the distance l and the scanning angle z to calculate lx respectively i ,ly i , 1x i =l*cos(z)(2), ly i=l*sin(z)(3), S2.3. Calculate the pose matrix of the reflector in the laser radar coordinate system as follows, (4), Calculate the pose matrix T of the reflector in the odometer coordinate system g as follows, (5), Calculate the pose matrix T of the reflector in the AGV coordinate system L as follows, T L =T g *T r (6).
[0015] The above settings can calculate the filtered point cloud coordinates through the distance l between the laser radar and the reflector and the scanning angle z respectively; the pose matrix of the reflector in the laser radar coordinate system can be obtained through the coordinates of the point cloud data , and then calculate the pose matrix T of the reflector in the odometer coordinate system g Finally, we get the pose matrix T of the reflector in the AGV coordinate system. L .
[0016] Furthermore, the step S3 also includes steps S3.1-S3.2: S3.1. If the AGV deviates from the straight path where the center position between the reflectors is located, then according to the pose matrix T of the reflector in the AGV coordinate system L Calculate the deviation error, and then control the AGV to return to the straight path. S3.1.1, take the straight path as the y-axis and the horizontal line where the AGV is located as the x-axis, and then establish a rectangular coordinate system. S3.1.2, according to the pose matrix T of the reflector in the AGV coordinate system L Determine the distance y0 that the AGV deviates from the y-axis, then select the deviation angle b0, and use the geometric relationship to calculate the distance S that the AGV travels to the y-axis, as follows: (7), S3.1.3, control the AGV to travel at a speed v0 along the deviation angle b0 and stop at a distance S, then control the AGV to rotate counterclockwise (90- b0)°, so that the AGV returns to the straight path after correcting the deviation error; S3.2: If the AGV does not deviate from the straight path where the center position between the reflectors is located, proceed to step S4.
[0017] The above setting can correct the deviation error of the AGV car from the straight path where the center position between the reflectors is located after matching the reflector contour, so that the AGV car can accurately return to the straight path.
[0018] Furthermore, the step S5 also includes steps S5.1-S5.2: S5.1. Calculate the position matrix T3 of the center point of the QR code in the odometer coordinate system as follows: (8); S5.2, by combining the position matrix T3 with the transformation matrix T2, calculate the position matrix T4 of the center point of the QR code in the AGV car coordinate system, as follows: T4= T2* T3 (9).
[0019] The above settings can calculate the position of the center point of the QR code in the AGV vehicle coordinate system.
[0020] Furthermore, the step S6 also includes the following contents: If the AGV is within the docking error range, the AGV completes the docking, thereby realizing the loading, unloading and transportation of materials; otherwise, the docking is performed again.
[0021] The above settings can enable the AGV to complete docking within the docking error range, thereby realizing the loading, unloading and transportation of materials. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] Figure 1 It is a flow chart of the working method of the present invention.
[0023] Figure 2 It is a geometric diagram of the calculation in the process of the AGV car correcting the deviation error in the present invention. DETAILED DESCRIPTION
[0024] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.
[0025] like Figure 1 As shown in the figure, a method for positioning and docking an AGV vehicle is provided. Reflective plates are provided on both sides in front of the machine platform. The length of the machine platform is preset to be c, the width of the machine platform is preset to be d, and the QR code is provided at the center position of the bottom of the machine platform. The distance to the center point of the QR code is directly determined by different coordinate system conversions to achieve positioning. The vehicle is driven from the middle position of the reflective plate to the bottom of the machine platform to scan the code for docking. The specific implementation examples and steps are as follows: S1, control the AGV to enter the reflector scanning area in front of the machine and switch to the reflector positioning mode, and then start matching the reflector contour. S1.1, Scan the point cloud data in the reflector area by the laser radar installed on the AGV, preset the point cloud intensity threshold T, weighting coefficients α, β, γ, S1.2, collecting the scanned point cloud data, and then filtering the point cloud data according to the preset intensity threshold T. In this embodiment, the intensity threshold T0 of the scanned point cloud data is compared with the preset intensity threshold T. If T0 is within the range of [0.6*T, 0.7*T], it is judged as the point cloud data of the reflector; otherwise, it is judged as other interfering point cloud data; S1.3. In the INS / GPC navigation system, the function is used to calculate the contour length error of the filtered point cloud data and the length of the reflector. Specifically, the err_length function is to determine the contour length of the point cloud data through the positioning system and then calculate the length error with the length information of the preset reflector. The center distance error between the filtered point cloud data and the reflector is calculated by the err_dist function. The err_dist function is to determine the error by the difference between the center of the point cloud data determined by the positioning system and the center of the preset reflector. The relative intensity error between the filtered point cloud data and the reflector is calculated by the cost_intensity function. The cost_intensity function determines the relative intensity error value by obtaining the intensity information of the point cloud data in the picture and the intensity information of the preset reflector. The evaluation function cost is used to determine whether the reflector contour matches. In this embodiment, the err_length function, the err_dist function, and the cost_intensity function are all existing functions and will not be repeated here. The formula of the evaluation function cost is as follows: cost=α* err_length+ β*err_dist+ γ*cost_intensity(1), If the reflector profile matches successfully, proceed to step S2; If the reflector profile is not matched successfully, the process returns to step S1.
[0026] S2. Obtain the pose matrix of the reflector in the laser radar coordinate system through the coordinates of the point cloud data , then according to the transformation matrix T of the laser radar in the odometer coordinate system b Get the pose matrix T of the reflector in the odometer coordinate system g , according to the transformation matrix T of the origin of the odometer coordinate system in the AGV vehicle coordinate system r Get the pose matrix T of the reflector in the AGV coordinate system L , S2.1, obtaining the distance l between the laser radar and the reflector and the scanning angle z in the laser radar scanning of step S1.1; S2.2, then use the distance l and the scanning angle z to calculate lx respectively i ,ly i , 1x i =l*cos(z)(2), ly i =l*sin(z)(3); S2.3, then determine the body angle through the posture sensor, and then obtain the posture matrix of the reflector in the lidar coordinate system through the coordinates of the point cloud data and the body angle value The pose matrix includes the horizontal and vertical coordinates of the two-dimensional space and the body angle information. In this embodiment, the pose matrix of the reflector in the laser radar coordinate system is The calculation formula is as follows. Since the mobile robot only moves in the plane, and the plane is the surface where the XY axis is located, and the mobile robot will not climb a slope; (4), Calculate the pose matrix T of the reflector in the odometer coordinate system g as follows, (5), Calculate the pose matrix T of the reflector in the AGV coordinate system L as follows, T L =T g *T r (6).
[0027] S3, according to the pose matrix T of the reflector in the AGV car coordinate system L Determine whether the AGV is on the straight path at the center of the reflectors. S3.1. If the AGV deviates from the straight path where the center position between the reflectors is located, then according to the pose matrix T of the reflector in the AGV coordinate system L Calculate the deviation error, and then control the AGV to return to the straight path. S3.1.1, take the straight path as the y-axis and the horizontal line where the AGV is located as the x-axis, and then establish a rectangular coordinate system; S3.1.2, according to the pose matrix T of the reflector in the AGV coordinate system L Determine the distance y0 that the AGV deviates from the y-axis, then select the deviation angle b0, and use the geometric relationship to calculate the distance S that the AGV travels to the y-axis. In this embodiment, the deviation angle b0 is set to 20°, as follows: (7); S3.1.3, control the AGV to travel at a speed v0 along the deviation angle b0 and stop at a distance S, and then control the AGV to rotate (90-b0)° in the direction of the straight path, which is counterclockwise in this embodiment, so that the AGV returns to the straight path after correcting the deviation error; S3.2: If the AGV does not deviate from the straight path where the center position between the reflectors is located, proceed to step S4.
[0028] S4. Taking the center of the reflector on one side of the machine as the origin, establish a reflector coordinate system, and then determine the position coordinates of the center point of the QR code in the reflector coordinate system as (x1, y1, z1) according to the length and width of the machine. S5. The transformation matrix between the reflector coordinate system and the odometer coordinate system is preset as T1. The position matrix T3 of the center point of the QR code in the odometer coordinate system can be obtained through the transformation matrix T1. The transformation matrix between the AGV coordinate system and the odometer coordinate system is preset as T2. The position matrix T3 is combined with the transformation matrix T2 to obtain the position matrix T4 of the center point of the QR code in the AGV coordinate system. S5.1. Calculate the position matrix T3 of the center point of the QR code in the odometer coordinate system as follows: (8); S5.2, by combining the position matrix T3 with the transformation matrix T2, calculate the position matrix T4 of the center point of the QR code in the AGV car coordinate system, as follows: T4= T2* T3 (9).
[0029] S6. Calculate the straight-line distance L0 between the center point of the QR code and the AGV through the position matrix T4, and then control the AGV to drive straight to the scanning area at the center of the bottom of the machine to achieve scanning docking.
[0030] The working principle of the present invention is as follows: the AGV is controlled to enter the reflector area in front of the machine, and then the reflector positioning mode is switched to scan the reflector, and then the point cloud data obtained by the scan is filtered according to the preset intensity threshold T, and the filtered point cloud data is judged as the point cloud data of the reflector, and then the contour length of the filtered point cloud data and the length error of the reflector are calculated by the err_length function, the center point error of the filtered point cloud data and the reflector are calculated by the err_dist function, and the relative intensity error of the filtered point cloud data and the reflector is calculated by the cost_intensity function. After the reflector contour is judged to be successfully matched by the evaluation function cost, the coordinates of the filtered point cloud data (lx i ,ly i ) and obtain the pose matrix of the reflector in the laser radar coordinate system , and then according to the transformation matrix T of the laser radar in the odometer coordinate system b Get the pose matrix T of the reflector in the odometer coordinate system g , according to the transformation matrix T of the origin of the odometer coordinate system in the AGV vehicle coordinate system r Get the pose matrix T of the reflector in the AGV coordinate system L At the same time, the reflector is in the AGV car coordinate system through the pose matrix T L Determine whether the AGV is on the straight path where the center position between the reflectors is located, so that the AGV can correct the deviation error from the straight path where the center position between the reflectors is located, so that the AGV can accurately return to the straight path, and then take the center of the reflector on one side of the machine as the origin, establish the reflector coordinate system and determine the position of the center point of the QR code in the reflector coordinate system, and then calculate the position matrix T3 of the center point of the QR code in the odometer coordinate system through the transformation matrix T1 of the reflector coordinate system and the odometer coordinate system. At the same time, the transformation matrix T2 of the AGV coordinate system and the odometer coordinate system is combined to obtain the position matrix T4 of the center point of the QR code in the AGV coordinate system, calculate the straight-line distance between the center point of the QR code and the AGV, and then control the AGV to drive in a straight line to the scanning area at the center position of the bottom of the machine to achieve scanning docking.
Claims
1. A method for positioning and docking an AGV vehicle, wherein reflectors are provided on both sides in front of a machine, the length of the machine is preset to be c, the width of the machine is preset to be d, a QR code is provided at the center of the bottom of the machine, and the distance to the center point of the QR code is directly determined by different coordinate system conversions to achieve positioning, and the vehicle drives from the middle position of the reflector into the bottom of the machine to scan the code for docking, and the method is characterized in that: The following steps are involved: S1, control the AGV to enter the reflector scanning area in front of the machine and switch to the reflector positioning mode, and then start matching the reflector contour; S1.
1. Scan the point cloud data in the reflector area by the laser radar set on the AGV, preset the point cloud intensity threshold T, weighting coefficients α, β, γ, S1.
2. Collect the scanned point cloud data, and then filter the point cloud data according to the preset intensity threshold T, S1.
3. Determine the error between the contour length of the filtered point cloud data and the length of the reflector, determine the center spacing error between the filtered point cloud data and the reflector, determine the relative intensity error between the filtered point cloud data and the reflector, and use the evaluation function cost to determine whether the reflector contour matches; the evaluation function cost is the weighted sum of the weighting coefficient and the length error, the center spacing error and the relative intensity error; S2. Obtain the pose matrix of the reflector in the laser radar coordinate system through the coordinates of the point cloud data , then according to the transformation matrix T of the laser radar in the odometer coordinate system b Get the pose matrix T of the reflector in the odometer coordinate system g , according to the transformation matrix T of the origin of the odometer coordinate system in the AGV vehicle coordinate system r Get the pose matrix T of the reflector in the AGV coordinate system L ; S3, according to the pose matrix T of the reflector in the AGV car coordinate system L Determine whether the AGV is on the straight path where the center position between the reflectors is located. If there is a deviation error, correct the deviation error to make the AGV return to the straight path where the center position between the reflectors is located; S4. Taking the center of the reflector on one side of the machine as the origin, establish a reflector coordinate system, and then determine the position coordinates of the center point of the QR code in the reflector coordinate system as (x1, y1, z1) according to the length and width of the machine. S5, preset the transformation matrix between the reflector coordinate system and the odometer coordinate system as T1, through the transformation matrix T1, the position matrix T3 of the center point of the two-dimensional code in the odometer coordinate system can be obtained, the transformation matrix between the AGV trolley coordinate system and the odometer coordinate system is preset as T2, and the position matrix T3 is combined with the transformation matrix T2 to obtain the position matrix T4 of the center point of the two-dimensional code in the AGV trolley coordinate system; S6. Calculate the straight-line distance between the center point of the QR code and the AGV through the position matrix T4, and then control the AGV to drive straight to the scanning area at the center of the bottom of the machine to achieve scanning docking.
2. The AGV positioning and docking method according to claim 1, characterized in that: The err_length function is used to calculate the error between the contour length of the filtered point cloud data and the length of the reflector. The err_dist function is used to calculate the center distance error between the filtered point cloud data and the reflector. The cost_intensity function is used to calculate the relative intensity error between the filtered point cloud data and the reflector. The evaluation function cost is used to determine whether the reflector contour matches.
3. The AGV positioning and docking method according to claim 1, characterized in that: The step S1.2 also includes: The intensity threshold T0 of the scanned point cloud data is compared with the preset intensity threshold T. If T0 is within the range of [0.6*T, 0.7*T], it is judged as the point cloud data of the reflector; otherwise, it is judged as other interfering point cloud data.
4. The AGV positioning and docking method according to claim 1, characterized in that: The step S1.3 also includes: The formula of the evaluation function cost is as follows: cost=α* err_length+ β*err_dist+ γ*cost_intensity(1).
5. The AGV positioning and docking method according to claim 1, characterized in that: The step S2 also includes calculating the coordinates of the filtered point cloud data (lx i ,ly i ), the specific steps are as follows: S2.
1. Obtain the distance l between the laser radar and the reflector and the scanning angle z from the laser radar scan. S2.2, then use the distance l and the scanning angle z to calculate lx respectively i ,ly i , lx i =l*cos(z)(2), ly i =l*sin(z)(3), S2.
3. Calculate the pose matrix of the reflector in the laser radar coordinate system as follows, (4), Calculate the pose matrix T of the reflector in the odometer coordinate system g as follows, (5), Calculate the pose matrix T of the reflector in the coordinate system of the mobile car L as follows, T L =T g *T r (6)。 6. The AGV positioning and docking method according to claim 1, characterized in that: The step S3 further comprises steps S3.1-S3.2: S3.
1. If the mobile car deviates from the straight path where the center position between the reflectors is located, then according to the position matrix T of the reflectors in the mobile car coordinate system L Calculate the deviation error, and then control the mobile car to return to the straight path. S3.1.1, take the straight path as the y-axis and the horizontal line where the mobile car is located as the x-axis, and then establish a rectangular coordinate system. S3.1.2, according to the pose matrix T of the reflector in the coordinate system of the mobile car L Determine the distance y0 that the mobile car deviates from the y-axis, then select the deviation angle b0, and use the geometric relationship to calculate the distance S that the mobile car travels to the y-axis, as follows: (7), S3.1.3, control the mobile car to travel at a speed v0 along the deviation angle b0 and stop at a distance S, then control the mobile car to rotate counterclockwise (90- b0)°, so that the mobile car returns to the straight path after correcting the deviation error; S3.
2. If the moving car does not deviate from the straight path where the center position between the reflective plates is located, the moving car is controlled to move along the straight path where the center position between the reflective plates is located and enter the bottom of the machine.
7. The AGV positioning and docking method according to claim 1, characterized in that: The step S5 also includes steps S5.1-S5.2: S5.
1. Calculate the position matrix T3 of the center point of the QR code in the odometer coordinate system as follows: (8); S5.2, by combining the position matrix T3 with the transformation matrix T2, calculate the position matrix T4 of the center point of the QR code in the AGV car coordinate system, as follows: T4= T2* T3 (9).
8. The AGV positioning and docking method according to claim 1, characterized in that: In step S6, Includes the following: If the AGV is within the docking error range, the AGV completes the docking, thereby realizing the loading, unloading and transportation of materials; otherwise, the docking is performed again.
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