Portable multi-sensor joint automatic calibration method

Abstract

The invention discloses a portable multi-sensor joint automatic calibration method, belongs to the technical field of automatic driving, and is suitable for multi-sensor joint automatic calibration in a non-fixed scene. Through combination of hardware platform design and a software calibration program, a portable calibration platform hardware device and multi-sensor joint automatic calibration are provided, cooperative mechanical arm hardware is added to enable the multi-sensor joint calibration process to be automatic, after mechanical arm precise pose control, relative pose constraint is added in the calibration process, and the calibration precision is improved. Moreover, the calculation amount is reduced through the RANSAC method, the optimization efficiency is improved, and finally, the calibration precision of the external parameters of the sensor is improved through the hardware setting of a portable calibration platform, so that the whole calibration process is simple, easy to use and efficient.

Description

Technical Field

[0001] The present invention belongs to the technical field of autonomous driving, and specifically relates to a portable multi-sensor joint automatic calibration method, which is suitable for multi-sensor joint automatic calibration in non-fixed scenarios. Background Art

[0002] In the existing field of joint calibration of autonomous driving multi-sensors, due to the assembly errors of sensor installation positions before different vehicles leave the factory, it is impossible to achieve complete uniformity, and there will be certain errors in the production and assembly process of sensor components, so multi-sensors must be uniformly collected and calibrated in the calibration workshop before leaving the factory. There are generally two common joint calibration methods:

[0003] The first is the markerless calibration method, which does not require a specific calibration plate or artificially constructed scenes. It generally performs automatic internal and external parameter calibration in outdoor natural scenes, but the vehicle is required to remain in motion during the calibration process. The advantage of this method is that the scene has a large degree of freedom and the calibration timing is flexible. The disadvantage is that natural scenes sometimes have no obvious characteristic markers, and the calibration accuracy cannot be guaranteed.

[0004] The second is the calibration method of markers in specific places. In specific scenarios, such as in the calibration workshop, the vehicle is parked in a specific position in the middle or on a rotating platform. Special calibration plates are attached around it according to a certain pattern or multiple mechanical arms are hung on the beam arm. A special calibration plate is fixed at the end of each mechanical arm. The program pre-sets the trajectory of the mechanical arm, and then starts the program to collect the camera and lidar data on the vehicle. Finally, the calibration algorithm is run to obtain the internal and external parameters of the multiple sensors. The advantage of this method is that since the calibration workshop is a relatively fixed environment, higher accuracy and more consistent sensor calibration can be achieved. For the mass production of smart driving vehicles, the calibration workshop is more convenient to form a standardized operating process. However, this type of method has strict requirements on the calibration site, and once the user replaces or re-disassembles a single sensor during use, the entire vehicle must be returned to the factory for recalibration. For customers, the cycle is long and the time cost is high. Especially for remote areas with weak infrastructure, the calibration and maintenance of multiple sensors of the entire vehicle is very difficult.

[0005] The innovation of the present invention is that the calibration platform hardware device is lightweight and portable, easy to disassemble and install, and can automatically carry out the multi-sensor calibration process in non-fixed scenarios with guaranteed calibration accuracy, greatly shortening the calibration cycle and reducing customer maintenance costs. Summary of the invention

[0006] (I) Purpose of the invention

[0007] The purpose of the present invention is to provide a portable multi-sensor joint automatic calibration method. Through the combination of hardware platform design and software calibration program, a portable calibration platform hardware device and multi-sensor joint automatic calibration are introduced. The present invention can solve the problem of returning the entire vehicle to the factory, thereby saving time and labor costs during transportation, and adds collaborative robotic arm hardware to make the multi-sensor joint calibration process automated, and effectively improve the calibration accuracy.

[0008] (II) Technical solution

[0009] A portable multi-sensor joint automatic calibration method is realized by combining software and hardware, that is, building a portable calibration platform hardware device and a multi-sensor joint automatic calibration program;

[0010] The hardware device of the portable calibration platform includes a tire holder, a scissor-type infinitely telescopic arm, and a six-degree-of-freedom robotic arm. Each component adopts a unified mechanical interface, and different components can be selected according to actual needs, and the quantity of the above components can be selected according to specific task requirements.

[0011] The tire holder adopts a double-screw clamp structure, which can be installed and fixed with high precision according to tires of different sizes. The tire holder has a built-in first laser ranging and receiving module to ensure that the front and rear wheels are facing the same direction as the vehicle body. A circular hanging ear is designed on the outer side of the cover of the first laser ranging and receiving module, which enables the tire holder to install the angle plate of the scissor-type infinitely telescopic arm in a horizontal or vertical posture.

[0012] The scissor-type infinitely telescopic arm is composed of an angle plate, a scissor-type telescopic structure, a mechanical arm fixing plate, and a laser ranging and receiving module; the angle plate is fixedly connected to the circular hanging ear structure, and the angle plate is designed with limit holes at 90°, 45°, and 0°, which are used to fix the scissor-type telescopic arm at different angles according to actual calibration requirements, so as to determine the relative position of the mechanical arm and the tire holder;

[0013] A second laser ranging and receiving module is installed on the robot arm fixing plate to transmit the relative position data from the center of the robot arm's axis to the wheel to the control center for later calibration. A mechanical installation interface for a six-degree-of-freedom robot arm is reserved on the robot arm fixing plate to enable modular installation of the robot arm.

[0014] The six-degree-of-freedom robotic arm selects the appropriate robotic arm model according to the specific size of the vehicle to be calibrated to meet the calibration requirements; a joint calibration plate is set at the end of the six-degree-of-freedom robotic arm for the joint calibration of the camera and lidar sensor;

[0015] During calibration, install one or two sets of tire holders on the front and rear tires on the same side of the vehicle to be calibrated, and connect the wiring harness to the control center equipment to power on;

[0016] Adjust the front and rear wheels of the vehicle to the same level according to the prompts of the laser ranging and receiving module;

[0017] According to the calibration requirements, one or more sets of scissor-type telescopic arms and motion execution terminals are selected for installation, and the data collection of the corresponding calibration board coverage area is completed by adjusting the installation positions of the scissor-type telescopic arms and motion execution terminals;

[0018] Start the multi-sensor, and the six-degree-of-freedom robot will move in conjunction with the calibration board according to the preset trajectory. Start the multi-sensor joint automatic calibration program to automatically collect multi-frame time-synchronized robot arm posture and multi-sensor data, and start automatic calibration of multi-sensor internal and external parameters. Repeat the six-degree-of-freedom robot until the accuracy reaches the standard and the calibration is completed;

[0019] The multi-sensor joint automatic calibration procedure completes the following actions:

[0020] Step 1, preparation before calibration;

[0021] Adjust the laser rangefinder to make the vehicle body, the connecting rod of the scissor-type telescopic structure and the six-degree-of-freedom robotic arm in a horizontal state:

[0022] Step 2: Calibrate the camera’s intrinsic parameters and the camera and lidar’s extrinsic parameters;

[0023] The relative posture constraints of the six-degree-of-freedom manipulator are introduced to improve the calibration accuracy, and the random sampling method is used to reduce the number of relative posture constraints and improve the calculation efficiency:

[0024] Step 3: Calibrate the external parameters of the laser radar relative to the vehicle body;

[0025] By presetting the robotic arm posture, the calibration plate and the robotic arm base are placed in a horizontal and vertical state respectively, so as to obtain the transformation matrix from the laser radar coordinate system to the vehicle body coordinate system, that is, the external parameters of the laser radar relative to the vehicle body.

[0026] (III) Effective income

[0027] 1. The present invention is light and portable, modular in structure, and easy to disassemble and install;

[0028] 2. The present invention has wide adaptability, strong scalability of the hardware platform device, modularity and scalability, and can adapt to various types and sizes of autonomous driving vehicles, such as trucks, cars, etc.;

[0029] 3. The present invention is flexible and can be applied to remote areas with weak infrastructure.

[0030] 4. After the introduction of the robotic arm, the high-precision posture information of the present invention can provide constraints for relative posture transformation, thereby improving the accuracy of external parameters between the camera and the laser radar;

[0031] 5. After the present invention adds the position and posture information of the robotic arm, according to the coordinate relationship designed by the hardware platform, it is possible to obtain the accurate transformation of the laser radar relative to the vehicle coordinate system, that is, the transformation from the laser radar coordinate system to the vehicle coordinate system;

[0032] 6. The overall cost of the present invention is lower than that of factory repair, and the cycle is short, the operation is simple, and it is easy to implement. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 Working diagram of the portable calibration platform of the present invention;

[0034] Figure 2 Schematic diagram of the working process of the present invention;

[0035] Figure 3 A schematic diagram of a tire fixing device of the present invention;

[0036] Among them: 11-double screw clamping block structure, 12-circular ear structure, 13-first laser ranging and receiving module

[0037] Figure 4 Schematic diagram of the scissor-type infinitely telescopic arm of the present invention;

[0038] Among them: 31-angle plate, 32-scissor-type telescopic structure, 33-mechanical arm fixing plate, 34-second laser ranging and receiving module

[0039] Figure 5 Schematic diagram of the six-degree-of-freedom robotic arm of the present invention;

[0040] Figure 6 Schematic diagram of the combined calibration plate of the present invention. DETAILED DESCRIPTION

[0041] The present invention is explained and illustrated in detail below with reference to the accompanying drawings and embodiments.

[0042] The multi-sensor joint automatic calibration referred to in the present invention mainly refers to the most common calibration between cameras and lidars. The calibration objects mainly include the intrinsic parameters of the camera, the extrinsic parameters of the camera and radar, and the extrinsic parameters from the sensor to the vehicle body.

[0043] The portable multi-sensor joint automatic calibration method of the present invention is realized by combining software and hardware, that is, the construction of a portable calibration platform hardware device and the implementation of a multi-sensor joint automatic calibration program. The present invention can solve the problem of multi-sensor joint automatic calibration of autonomous driving vehicles in non-fixed scenes. Compared with the existing calibration method in a fixed place, it has the advantages of flexibility and convenience.

[0044] 1. Hardware setup of portable calibration platform

[0045] The portable calibration platform hardware device of the present invention is as follows: Figure 1 As shown, it includes two tire fixers 1, a scissor-type infinitely telescopic arm 3, and a set of six-degree-of-freedom mechanical arms 4. Each component adopts a unified mechanical interface, and different components can be selected according to actual needs, not limited to the number of the above components. The tire fixer 1 adopts a double-screw clamping block structure 11, such as Figure 3 As shown, it can be installed and fixed with high precision according to tires of different sizes. It has a built-in first laser ranging and receiving module 13 to ensure that the front and rear wheels are facing the same direction as the vehicle body. The principle is that the laser module on one tire holder illuminates the laser receiver on another tire holder to adjust the steering wheel. When the laser receiving module reads correctly, it indicates that the front and rear wheels are facing the same direction as the vehicle body, which is conducive to the calibration of external parameters of the multi-sensor to the vehicle body coordinate system. A circular hanging ear 12 is designed on the outside of the cover plate of the first laser ranging and receiving module, which enables the tire holder 1 to install the angle plate of the scissor-type infinitely telescopic arm 3 in a horizontal or vertical posture; the scissor-type infinitely telescopic arm 3 is composed of four parts: an angle plate 31, a scissor-type telescopic structure 32, a mechanical arm fixing plate 33, and a laser ranging and receiving module 34. Figure 4 The angle plate 31 can be fixedly connected with the circular ear structure 12 in the tire fixer assembly 1. The angle plate 31 is designed with limiting holes at several angles such as 90°, 45°, and 0°, so that the scissor-type telescopic arm can be fixed at different angles according to actual calibration requirements, so as to determine the relative position of the mechanical arm and the tire fixer;

[0046] The scissor-type telescopic structure 32 adopts a hollow wiring design of 7075 aviation aluminum, and the wire trough is designed on the inner side of each connecting rod, which ensures the safety of the wire without affecting the telescopic movement. A second laser ranging and receiving module 34 is installed on the robot arm fixing plate 33, which is used to transmit the relative position data from the center of the robot arm's axis to the wheel to the control center for later calibration. The principle is to measure the relative distance between the coordinates of the base of the robot arm fixing plate and the vehicle body, which is convenient for the calibration of the external parameters of the sensor and the vehicle body. The mechanical installation interface of the six-degree-of-freedom robot arm 4 is reserved on the robot arm fixing plate 33, which enables the robot arm to be installed modularly.

[0047] The six-degree-of-freedom mechanical arm 4 selects a suitable mechanical arm model according to the specific size of the vehicle 2 to be calibrated to meet the calibration requirements. A joint calibration plate 5 is provided at the end of the six-degree-of-freedom mechanical arm 4, such as Figure 5 , 6 As shown, the joint calibration board is used for joint calibration of sensors such as cameras and lidars. The four corners of the calibration board are hollow circles, and the middle area is a common checkerboard image. The calibration board is hard-connected to the end of the six-degree-of-freedom robotic arm 4.

[0048] The calibration process of the portable calibration platform hardware device is as follows: Figure 2 shown.

[0049] First, install one or two sets of tire holders on the front and rear tires on the same side of the vehicle to be calibrated, connect the wiring harness to the control center equipment and power it on.

[0050] Adjust the front and rear wheels of the vehicle to the same level according to the prompts of the laser ranging and receiving module.

[0051] According to the calibration requirements, one or more sets of scissor-type telescopic arms and motion execution terminals are selected and installed, and the data collection of the corresponding calibration board coverage area is completed by adjusting the installation positions of the scissor-type telescopic arms 3 and the motion execution terminals, such as left front, right front, left rear, and right rear;

[0052] Start the multi-sensor, the six-degree-of-freedom robot 4 will move in conjunction with the calibration plate 5 according to the preset trajectory, start the multi-sensor joint automatic calibration program to automatically collect multi-frame time-synchronized robot arm posture and multi-sensor data, and start automatic calibration of the multi-sensor internal and external parameters. If the calibration accuracy is not reached, repeat the operation of the six-degree-of-freedom robot 4. If the calibration accuracy is achieved, the calibration process is completed and the six-degree-of-freedom robot stops at the initial position.

[0053] (II) Multi-sensor joint automatic calibration procedure

[0054] For the typical joint calibration problem of camera and lidar sensors for self-driving cars, the main problems to be solved are the intrinsic parameters of the camera, the extrinsic parameters from the camera coordinate system to the lidar coordinate system, and the extrinsic parameters from the lidar coordinate system to the vehicle coordinate system. The automatic calibration method mainly corresponds to Figure 2 In the process of collecting multi-frame robot arm pose and multi-sensor data, and starting automatic calibration, two modules are included. Note that the end of the robot arm is hard-connected to the calibration plate, so the pose of the calibration plate can be obtained from the pose of the robot arm. Therefore, in the description of the calibration method, if no specific explanation is given, the pose data of the calibration plate or the robot arm can be regarded as the same data.

[0055] The automatic calibration method adopted by the present invention mainly includes three parts.

[0056] Part 1: Preparation before calibration. Adjust the laser rangefinder so that the vehicle body, connecting rod and robotic arm module are as horizontal as possible:

[0057] In this method, first drive the vehicle to the flattest possible ground, not limited to indoors or outdoors, adjust the rear wheel laser ranging module so that it can transmit signals to the front wheel laser receiving module, set the signal feedback reception successfully, indicating that the front and rear wheels are adjusted to be consistent with the vehicle body; at the same time, adjust the posture of the robot arm fixing plate so that its laser receiving module can receive the front wheel laser emission signal, indicating that the robot arm fixing plate is also level with the vehicle body, and the next calibration operation can be continued;

[0058] The second part is the calibration of camera intrinsic parameters, camera and lidar extrinsic parameters. The relative pose constraints of the robot arm are introduced to improve the calibration accuracy, and the random sample consensus (RANSAC) method is used to reduce the number of relative pose constraints and improve the calculation efficiency:

[0059] When calculating the relative transformation projection error, considering that the introduction of the relative posture transformation constraint of the robot arm can improve the calibration accuracy, but the amount of calculation also increases sharply, the random sampling consensus (RANSAC) method is adopted, that is, part of the relative posture constraints are randomly extracted in an iterative manner to optimize the solution variables, so as to achieve the purpose of improving the calculation efficiency.

[0060] The third part is the external parameter calibration of the laser radar relative to the vehicle body. By presetting the robotic arm posture, the calibration plate and the robotic arm base are successively in a horizontal and vertical state, so as to obtain the transformation matrix from the laser radar coordinate system to the vehicle body coordinate system, that is, the external parameters of the laser radar relative to the vehicle body:

[0061] The main steps are as follows:

[0062] 1. According to the preset procedure of laser radar external parameter calibration, the robotic arm automatically adjusts its posture so that the calibration plate and the robotic arm base are in a horizontal state, and the laser radar point cloud data is collected at this time;

[0063] 2. According to the method of calculating the 3D coordinates of the center of the hollow circle in the lidar point cloud in the second part, the 3D coordinates of the center are calculated, denoted as O = [x0, y0, z0], and the point cloud data of the calibration plate area in the lidar point cloud is extracted, and the unit normal vector of the plane point cloud is estimated, denoted as

[0064] 3. Adjust the robot arm posture so that the calibration plate and the robot arm base are vertical, and collect the lidar point cloud data again;

[0065] 4. Extract the point cloud data of the calibration plate area in the lidar point cloud and estimate the unit normal vector of the plane point cloud, recorded as

[0066] 5. At this time, take O = [x0, y0, z0] as the coordinate origin, as well as and The cross product of are three coordinate axes, forming the calibration plate coordinate system O b , its position relative to the laser radar coordinate system is expressed as Where R LO and t LOrepresents the rotation and translation of the calibration plate coordinate system relative to the lidar coordinate system, P LO It is a 4×4 matrix, which represents the transformation from the calibration plate coordinate system to the lidar coordinate system;

[0067] 6. According to the mechanical dimensions of the calibration plate and the geometric relationship between the robotic arm, the relative transformation of the calibration plate center coordinates to the robotic arm base can be calculated. According to the structure of the portable calibration platform hardware device in this method, the transformation of the calibration plate coordinate system relative to the vehicle coordinate system can be known, which is recorded as Where R VO and t VO represents the rotation and translation of the calibration plate coordinate system relative to the lidar coordinate system, P VO Indicates the transformation from the calibration plate coordinate system to the vehicle body coordinate system;

[0068] 7. Let the transformation matrix from the laser radar coordinate system to the vehicle coordinate system be P VL , from the relative transformation relationship of the coordinate system, we can know that in Represents the transformation matrix P LO So far, we get the external parameter calibration P of the variable laser radar relative to the vehicle body. VL .

[0069] In summary, through the three-part calibration process, the calibration of camera intrinsic parameters, extrinsic parameters from camera coordinate system to lidar coordinate system, and extrinsic parameters from lidar coordinate system to vehicle coordinate system are completed.

[0070] The advantage of the method of the present invention is that after the introduction of precise posture control of the robotic arm, relative posture constraints are added to the calibration process, and the amount of calculation is reduced through the RANSAC method, thereby improving the optimization efficiency. Finally, the hardware setting of the portable calibration platform is used to improve the calibration accuracy of the sensor extrinsic parameters, making the entire calibration process simple, easy to use and efficient.

[0071] The above contents are further detailed descriptions of the present invention in combination with specific implementation methods, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A portable multi-sensor joint automatic calibration method, characterized in that: This is achieved through the combination of software and hardware, i.e. the construction of a portable calibration platform hardware device and a multi-sensor joint automatic calibration program; The portable calibration platform hardware device includes a tire holder, a scissor-type infinitely telescopic arm, and a six-degree-of-freedom robotic arm; each component adopts a unified mechanical interface, and different components can be selected according to actual needs, and the quantity of the above components can be selected according to specific task requirements; The tire holder adopts a double-screw clamp structure, which can be installed and fixed with high precision according to tires of different sizes. The tire holder has a built-in first laser ranging and receiving module to ensure that the front and rear wheels are facing the same direction as the vehicle body. A circular hanging ear is designed on the outer side of the cover of the first laser ranging and receiving module, which enables the tire holder to install the angle plate of the scissor-type infinitely telescopic arm in a horizontal or vertical posture. The scissor-type infinitely telescopic arm is composed of an angle plate, a scissor-type telescopic structure, a mechanical arm fixing plate, and a laser ranging and receiving module; the angle plate is fixedly connected to the circular hanging ear structure, and the angle plate is designed with limit holes at 90°, 45°, and 0°, which are used to fix the scissor-type telescopic arm at different angles according to actual calibration requirements, so as to determine the relative position of the mechanical arm and the tire holder; A second laser ranging and receiving module is installed on the robot arm fixing plate to transmit the relative position data from the center of the robot arm's axis to the wheel to the control center for later calibration. A mechanical installation interface for a six-degree-of-freedom robot arm is reserved on the robot arm fixing plate to enable modular installation of the robot arm. The six-degree-of-freedom robotic arm selects the appropriate robotic arm model according to the specific size of the vehicle to be calibrated to meet the calibration requirements; a joint calibration plate is set at the end of the six-degree-of-freedom robotic arm for the joint calibration of the camera and lidar sensor; The calibration process of the portable calibration platform hardware device is as follows: Step 1: During calibration, install one or two sets of tire holders on the front and rear tires on the same side of the vehicle to be calibrated, connect the wiring harness to the control center equipment and power on; Step 2: Adjust the front and rear wheels of the vehicle to the same level according to the prompts of the laser ranging and receiving module; Step 3: Select and install one or more sets of scissor-type telescopic arms and motion execution terminals according to the calibration requirements, and complete the data collection of the corresponding calibration board coverage area by adjusting the installation positions of the scissor-type telescopic arms and motion execution terminals; Step 4: Start the multi-sensor, and the six-degree-of-freedom robotic arm will move in conjunction with the calibration board according to the preset trajectory. Start the multi-sensor joint automatic calibration program to automatically collect multi-frame time-synchronized robotic arm posture and multi-sensor data, and start automatic calibration of the internal and external parameters of the multi-sensor. Repeat the operation of the six-degree-of-freedom robotic arm until the accuracy reaches the standard and the calibration is completed. The multi-sensor combined automatic calibration procedure completes the following actions: Step 1, preparation before calibration; Adjust the laser rangefinder to make the vehicle body, the connecting rod of the scissor-type telescopic structure and the six-degree-of-freedom robotic arm in a horizontal state: Step 2: Calibrate the camera’s intrinsic parameters and the camera and lidar’s extrinsic parameters; The relative posture constraints of the six-degree-of-freedom manipulator are introduced to improve the calibration accuracy, and the random sampling method is used to reduce the number of relative posture constraints and improve the calculation efficiency: Step 3: Calibrate the external parameters of the laser radar relative to the vehicle body; By presetting the robotic arm posture, the calibration plate and the robotic arm base are placed in a horizontal and vertical state respectively, so as to obtain the transformation matrix from the laser radar coordinate system to the vehicle body coordinate system, that is, the external parameters of the laser radar relative to the vehicle body.

2. A portable multi-sensor joint automatic calibration method according to claim 1, characterized in that: Step 3 of the multi-sensor joint automatic calibration procedure specifically includes the following steps: 3.1 According to the preset procedure of laser radar external parameter calibration, the robotic arm automatically adjusts its posture so that the calibration plate and the robotic arm base are in a horizontal state, and the laser radar point cloud data is collected at this time; 3.2 According to the method of the three-dimensional coordinates of the center of the hollow circle in the laser radar point cloud, the three-dimensional coordinates of the center are calculated, denoted as O = [x0, y0, z0], and the point cloud data of the calibration plate area in the laser radar point cloud is extracted, and the unit normal vector of the plane point cloud is estimated, denoted as 3.3 Adjust the robot arm posture so that the calibration plate and the robot arm base are in a vertical state, and collect the lidar point cloud data again; 3.4 Extract the point cloud data of the calibration plate area in the lidar point cloud and estimate the unit normal vector of the plane point cloud, denoted as At this time, take O = [x0, y0, z0] as the coordinate origin, as well as and The cross product of are three coordinate axes, forming the calibration plate coordinate system O b , its position relative to the laser radar coordinate system is expressed as Where R LO and t LO represents the rotation and translation of the calibration plate coordinate system relative to the lidar coordinate system, P LO It is a 4×4 matrix, which represents the transformation from the calibration plate coordinate system to the lidar coordinate system; 3.5 According to the mechanical dimensions of the calibration plate and the geometric relationship between the robotic arm, the relative transformation of the calibration plate center coordinates to the robotic arm base is calculated. According to the structure of the portable calibration platform hardware device, the transformation of the calibration plate coordinate system relative to the vehicle coordinate system is obtained, which is recorded as Where R VO and t VO represents the rotation and translation of the calibration plate coordinate system relative to the lidar coordinate system, P VO Indicates the transformation from the calibration plate coordinate system to the vehicle body coordinate system; 3.6 Let the transformation matrix from the laser radar coordinate system to the vehicle coordinate system be P VL , from the relative transformation relationship of the coordinate system, we can know that in Represents the transformation matrix P LO So far, we get the external parameter calibration P of the unknown variable laser radar relative to the vehicle body. VL .

3. A portable multi-sensor joint automatic calibration method according to claim 1 is characterized in that the scissor-type telescopic structure adopts a hollow wiring design of 7075 aviation aluminum, and the wire groove is designed on the inner side of each connecting rod, which ensures the safety of the wire without affecting the telescopic structure.

4. A portable multi-sensor joint automatic calibration method according to claim 1, characterized in that: The four corners of the calibration plate are hollow circles, the middle area is a common chessboard image, and the calibration plate is hard-connected to the end of the six-degree-of-freedom robotic arm 4.

5. A portable multi-sensor joint automatic calibration method according to claim 1, characterized in that: Step 1 of the multi-sensor joint automatic calibration procedure is as follows: drive the vehicle to a flat ground, not limited to indoors or outdoors, adjust the rear wheel laser ranging module so that it can transmit signals to the front wheel laser receiving module, set the signal feedback reception successfully, indicating that the front and rear wheels are adjusted to be consistent with the vehicle body; at the same time, adjust the posture of the robotic arm fixing plate so that the laser receiving module can receive the front wheel laser emission signal, indicating that the robotic arm fixing plate is also level with the vehicle body, and the next calibration operation can be continued.

6. A portable multi-sensor joint automatic calibration method according to claim 1, characterized in that: In step 2 of the multi-sensor joint automatic calibration procedure, when calculating the relative transformation projection error, a random sampling consensus method is used to randomly extract some relative pose constraints in an iterative manner to optimize the solution variables, thereby achieving the purpose of improving the calculation efficiency.

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