Laser radar internal reference calibration method and internal reference calibration system

Abstract

The invention provides a laser radar internal reference calibration method, which comprises a calibration data acquisition step of acquiring multi-frame point cloud data of different relative positions between a laser radar and a reflection plane of a target plate in a rated working range of the laser radar, and simultaneously, when each frame of point cloud data corresponds to the point cloud data, acquiring a calibration data corresponding to each frame of point cloud data; acquiring a space plane equation of the reflection plane 21 through the camera array; an internal reference resolving step: the target of internal reference calibration in the internal reference optimization model is to minimize the distance between a point on each calibration target plate and a target plate plane measured by the laser radar; and calculating the optimal solution of the system under the constraint condition by using a mathematical optimization algorithm to determine the calibration parameters of the laser radar. According to the laser radar internal reference calibration method, a global internal reference integration calibration method is provided, and the internal reference balancing the correction precision under different scanning distances and scanning inclination angles is obtained, so that the performance of the laser radar in a rated scanning range is well balanced, and the performance precision is prevented from being obviously reduced under the edge condition.

Description

Technical Field

[0001] The present invention relates to the technical field of laser radar calibration, and in particular to a laser radar internal parameter calibration method and an internal parameter calibration system. Background Art

[0002] As an important part of modern sensor technology, LiDAR has been widely used in autonomous driving, robotics, terrain mapping and other fields. LiDAR calculates the distance, speed and direction of the target by emitting laser pulses and receiving the signals reflected by the object. However, due to installation, manufacturing and structural constraints, there is a certain error between the actual measurement value and the theoretical value. In order to ensure the measurement accuracy and reliability of LiDAR, accurate internal calibration of LiDAR is essential. Existing LiDAR calibration methods often rely on complex physical environment construction and cumbersome manual adjustments, which is not only time-consuming and labor-intensive, but also difficult to ensure the consistency and accuracy of the calibration results. Summary of the invention

[0003] In order to improve the accuracy of laser radar internal parameter calibration and optimize the operation process of laser radar internal parameter calibration, the present invention provides a laser radar internal parameter calibration method and an internal parameter calibration system.

[0004] The present application provides a laser radar internal parameter calibration method, comprising: S1. Calibration data acquisition step: obtain multiple frames of point cloud data at different relative positions between the laser radar and the reflection plane of the target plate within the rated working range of the laser radar, where each frame of point cloud data is recorded as pc , the number of point cloud data frames is recorded as q At the same time, corresponding to each frame of point cloud data, the spatial plane equation of the reflection plane 21 is obtained through the camera array 3 n ; For each frame of point cloud data, the calibration data is obtained d =( pc , n ). So the calibration data set can be expressed as ; S2. Internal parameter calculation steps: The calibration parameters are α =( d ρ , d θ , d φ , s , h , v ),( d ρ , d θ , d φ) is the distance, horizontal angle and vertical angle of the laser radar ( r , i , f ), s is the distance measurement scale factor, h and v To receive the horizontal and vertical offsets of the system from the origin of the device, The correction equation of the calibrated measurement value is:

[0005] The goal of the internal parameter calibration in the internal parameter optimization model is to minimize the distance between each point on the calibration target plate measured by the lidar and the target plate plane. The objective function of the internal parameter optimization model is defined as:

[0006] In the formula, P and Q k The calibration data obtained in the calibration data acquisition process, P is the set of all measured planes, Q k is the set of all points on the plane, d ( q , p k )for Q k midpoint q To plane p k Distance:

[0007] In the above formula, x i , y i , z i For point q The coordinates of the measured values ​​are corrected by the calibration parameters α =( d ρ , d θ , d φ , s , h , v )Sure; The optimal solution of the above system under the constraints is solved by mathematical optimization algorithm to determine the calibration parameters of the lidar. α =( d ρ , d θ, d φ , s , h , v ).

[0008] Preferably, the S1 calibration data acquisition step is specifically as follows: S11, adjust the laser radar inclination angle to i 1 ; Control the distance between the laser radar and the target plate to the set distance p 1 ; Collecting laser radar i 1 Scanned at an angle p 1 Position target plate S Frame point cloud data, denoted as ; Calibration data in the current state , where n 1 are the spatial plane equation parameters of the target plate in the current state.

[0009] S12, repeat S11 step, collect N The target scanning data of the laser radar within the preset distance interval between the target and the target and the spatial plane equation parameters of the corresponding target are combined to form a calibration data set ; S13, repeat steps S11-S12, collect M The laser radar scanning data of the target plate in the preset inclination range and the spatial plane equation parameters of the corresponding target plate are combined to form a complete calibration data set Q = .

[0010] Preferably, the space plane equation parameters of the target plate in the current state in the S1 calibration data acquisition step are obtained by solving the images obtained by imaging the reflection plane respectively by several cameras in the camera array at this time.

[0011] Preferably, the preset distance interval is 0.5-50m, and / or the preset inclination angle interval is -45-45°.

[0012] Preferably, the mathematical optimization algorithm in the S2 internal parameter solution step is the Levenberg-Marquardt algorithm.

[0013] Preferably, after the S2 internal parameter solution step is completed, the S3 internal parameter verification step is also executed: the relative position change between the target plate and the laser radar is controlled, and multiple frames of point cloud data corresponding to the reflection plane corrected by the calibration parameters are obtained. At the same time, the spatial plane equation of the reflection plane is obtained for each frame of point cloud data, and the average error of the point cloud data to the corresponding spatial plane equation is counted.

[0014] Preferably, if the average error is outside the threshold range, the calibration data acquisition step S1 and the internal parameter solution step S2 are repeated to perform recalibration until the average error is within the threshold range.

[0015] The present application also provides a laser radar internal parameter calibration system, comprising: LiDAR, which has a fixed position; The target plate has a varying spatial distance relative to the laser radar; a reflective plane with a finite area; The camera array includes a plurality of cameras, and the cameras are used to combine and determine the spatial plane equation of the reflection plane.

[0016] Preferably, the laser radar can rotate around a fixed point in space, or the reflection plane can rotate around a fixed point in space.

[0017] Preferably, the target plate is movably arranged on a guide rail via a fixing frame; the guide rail extends in a direction away from the laser radar. Or, the target plate is placed on a fixed frame in a controlled rotational manner. Alternatively, the target plate is movably arranged on a guide rail via a fixed frame; the guide rail extends in a direction away from the laser radar, and the cameras in the camera array are divided into two groups, the two groups of cameras are placed on both sides of the guide rail, and the cameras in each group are arranged in sequence along the extension direction of the guide rail.

[0018] The laser radar internal parameter calibration method and internal parameter calibration system of the present application realize the automated calibration of the laser radar. Through a pre-set process, the automated unmanned calibration of the laser radar can be realized. Compared with the existing laser radar calibration methods, the calibration efficiency can be significantly improved and the labor input can be reduced.

[0019] The lidar internal parameter calibration method of the present application provides a global internal parameter integration calibration method, which can take into account the different scanning conditions of the lidar and obtain internal parameters that balance the correction accuracy under different scanning distances and scanning inclinations, thereby achieving a better balance in the performance of the lidar within the rated scanning range and avoiding a significant decrease in performance accuracy in edge cases. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a schematic diagram of the architecture of the laser radar internal calibration system of this application; Figure 2 This is a schematic diagram of the structure of the laser radar internal calibration system of this application; Figure 3 A schematic diagram of the driving of the target plate movement in the laser radar internal reference calibration system of the present application; Figure 4 This is a schematic diagram of the overall process of the laser radar internal parameter calibration method of this application; Figure 5A schematic diagram of the automated calibration process of the laser radar internal calibration system of this application; Figure 6 It is a schematic diagram of the reflection plane 21 of the target plate 2 in the laser radar internal reference calibration system of the present application.

[0021] In the figure, 1: LiDAR; 11: Calibration platform; 12: Pan / tilt; 2: Target plate; 21: Reflection plane; 22: Guide rail; 23: Fixing bracket; 3: Camera array; 31: Camera; 51: Integrated control unit; 52: Communication unit; 53: Computing and storage unit. DETAILED DESCRIPTION

[0022] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. In this specification, the size ratios in the drawings do not represent the actual size ratios, but are only used to reflect the relative position relationship and connection relationship between the components. Components with the same name or the same number represent similar or identical structures and are only for illustrative purposes.

[0023] This application mainly provides a highly automated laser radar calibration system and a corresponding laser radar internal parameter calibration method. Figure 1 This is a schematic diagram of the architecture of the LiDAR calibration system. Figure 2 It is a structural diagram of the lidar calibration system.

[0024] LiDAR internal calibration system Figure 1 As shown, it includes a laser radar 1 with a fixed position and a target plate that is arranged movably, and also includes a camera array 3 for determining the precise spatial position of the target plate 2. The position of the laser radar 1 is fixed, and optionally, its posture is variable, that is, it can be rotated in a fixed point space. The target plate 2 provides a limited area reflection plane 21 to reflect the laser of the laser radar 1. The target plate 2 can at least translate in space to change the relative position with the target plate 2. The target plate 2 is preferably posture-variable, that is, it rotates around a fixed point space to change the orientation of the reflection plane 21. The camera array 3 includes a number of reasonably arranged cameras 31 to determine the position and orientation of the reflection plane 21 based on the combined imaging of the camera 31, which is the plane equation of the reflection plane 21 in the spatial coordinate system. In order to ensure the precise determination of the specific position of the reflection plane 21 in the image taken by the camera 31, a number of checkerboards are set on the surface of the reflection plane 21. The checkerboard is preferably placed at the four corners of the reflection plane 21. The target plate 2 is a rectangular flat plate with a flat surface and coated with a high laser reflectivity paint, which provides a stable reflection signal for the laser radar calibration. The four corners of the target plate 2 have camera array tags, which provide feature points for the camera array. It can be understood that the movement of the target plate 2 is equivalent to the posture change of the laser radar 1 to a certain extent. In other words, when the orientation of the target plate 2 is ignored, the posture change of the laser radar 1 can be equivalent to the displacement of the target plate 2 in the same direction.

[0025] The purpose of setting a plurality of cameras 31 in the camera array 3 is to solve the spatial stereoscopic position of the reflection plane 21 through the plane imaging of the plurality of cameras 31 in space, and obtain the spatial plane equation of the reflection plane 21. Another purpose is to ensure that the camera 31 is always within a reasonable distance from the target plate 2 within the motion range of the target plate 2 through reasonable layout, thereby improving the positioning accuracy of the target plate 2 within the motion range.

[0026] Figure 2 A structural diagram of a laser radar calibration system that meets the above conditions is given. A calibration platform 11 is set in the calibration space, and the laser radar 1 is set on the calibration platform 11 for fixed-point movement. The calibration platform 11 is a device for supporting and adjusting the position and posture of the laser imaging radar equipment. The laser radar 1 is set on the calibration platform 11 through a gimbal 12. The gimbal 12 provides multiple degrees of freedom of movement, which can enable the laser radar to be accurately leveled in multiple degrees of freedom to meet the requirements of the laser radar internal parameter calibration. Preferably, the pitch and left and right swing of the laser radar 1 are guaranteed.

[0027] The target plate 2 is movably arranged on the guide rail 22 via the fixing frame 23. The guide rail 22 extends in a direction away from the laser radar 1, and when the fixing frame 23 is controlled to move on the guide rail 22, the relative distance between the reflection plane 21 and the laser radar 1 is changed. The target plate 2 is preferably arranged on the fixing frame 23 to rotate in a controlled manner, that is, the specific orientation of its reflection plane 21 on the fixing frame 23 can be controlled and adjusted. Figure 3 Schematic diagram of the motion mechanism of the target plate 2. The movement of the fixed frame 23 on the guide rail 22 is realized by the gear rack transmission driven by the stepper motor, and the posture change of the target plate 2 on the fixed frame 23 is realized by the worm gear mechanism driven by the stepper motor. The target plate 2 provides a stable target for the laser radar internal calibration, ensuring the accuracy and reliability of the internal calibration.

[0028] The distance between the target plate 2 and the laser radar 1 can be adjusted by adjusting the distance of the target plate 2, and the angle of the reflection surface in different scenes can be simulated by changing the orientation of the target plate 2. At the same time, the variable posture of the laser radar 1 ensures that any scanner on the laser radar 1 can always obtain its effective reflection point on the reflection plane 21 through combined control to achieve the purpose of posture correction.

[0029] The cameras 31 are divided into two groups, and the two groups are placed on both sides of the guide rail 22. The cameras 31 in each group are arranged in sequence along the extension direction of the guide rail 22. The figure shows the situation of three cameras in each group. At any position of the target plate 2, at least two opposite cameras 31 can image the reflection plane 21 to solve the spatial plane equation of the reflection plane 21. In most cases, four to six groups of cameras 31 can image the reflection plane 21 to improve the displacement solution accuracy of the reflection plane 21. Extending along the guide rail 22 is mainly to ensure that there is a camera 31 close to the target plate 2 in the entire range of movement of the target plate 2 along the guide rail 22 to ensure accuracy.

[0030] The camera array 3 includes six cameras, which are fixedly installed in the experimental environment and distributed on both sides of the motion guide rail. By identifying and measuring the visual positioning tags fixed on the target board, the real-time and accurate measurement of the plane pose (i.e., the plane equation parameters) of the target board 2 is achieved. A plurality of visual identifiers are set on the target board 2, and the visual identifiers have identifiable geometric features so as to be captured by the camera array. Each camera is calibrated with internal and external parameters to obtain the internal parameters of each camera and its position and posture information relative to the global coordinate system. The images of the visual identifiers on the target board 2 in each camera are collected, and the visual identifiers in each image are detected and matched. According to the matching of the visual identifiers in the images of each camera, the three-dimensional coordinates of the visual identifiers in the global coordinate system are calculated. Using the three-dimensional coordinate information of the visual identifier, the least squares method is used to calculate the equation of the spatial plane where the target board 2 is located. The spatial plane equation is expressed as ax+by+cz+d=0, where a, b and c are the normal vector components of the plane, and d represents the distance from the plane to the origin. The parameters a, b, c, and d of the target plate 2 plane equation measured by the camera array 3 provide high-precision visual auxiliary information for the internal calibration of the laser radar 1.

[0031] The computing storage unit 53 is a computer that integrates a high-performance processor and a storage unit. It is responsible for solving, analyzing and storing the received laser radar data, and running the calibration algorithm to solve the internal parameters of the laser radar. The comprehensive control unit 51 is responsible for the coordinated control of the entire calibration system. The communication unit 52 is responsible for providing a data transmission channel, including the motion control of the fixed frame 23, the motion control of the target plate 2, the data reading of the camera array 3, and the real-time transmission of the laser radar 1 data.

[0032] The laser radar internal parameter calibration algorithm of the present application is applied to the above laser radar internal parameter calibration system. Figure 1 As shown, the steps include: S1, calibration data acquisition step. Multiple frames of point cloud data at different relative positions between the laser radar 1 and the reflection plane 21 are acquired within the rated working range of the laser radar, where each frame of point cloud data is recorded as pc, and the number of point cloud data frames is recorded as q; at the same time, corresponding to each frame of point cloud data, the spatial plane equation n of the reflection plane 21 is acquired through the camera array 3. For each frame of point cloud data, the calibration data d=(pc,n) is synthesized. So the calibration data set can be expressed as .

[0033] Specifically, S11, install the laser radar to be calibrated on the calibration platform 11 through the pan-tilt, and adjust the angle of the pan-tilt so that the laser radar to be calibrated and the calibration platform form a certain angle i 1 Through the integrated control unit and the communication unit, the control frame 23 carries the target plate 2 and moves to a specific position along the guide rail 22 p 1 Through the integrated control unit 51 and the communication unit 52, the laser radar 1 to be calibrated is collected i 1 Scanned at an angle p 1 Position target plate 2 S Frame point cloud data, denoted as Through the integrated control unit 51 and the communication unit 52, the camera array 3 is controlled to solve the plane equation parameters of the target plate 2 relative to the global coordinate system in the current state ; The calibration data in the current state is stored by the calculation storage unit (210) .

[0034] S12, repeat the above S11 step, collect N The target plate 2 scanning data and corresponding plane equation parameters of the laser radar 1 to be calibrated within the preset distance interval between the laser radar 1 and the target plate 2 are combined to form a calibration data set ; S13, repeat steps S11-S12, collect M The scanning data of the target plate 2 of the laser radar 1 to be calibrated within the preset inclination range and the corresponding plane equation parameters are combined to form a complete calibration data set ; For general laser radars, the preset distance range is 0.5-50m, and the preset inclination angle range is -45-45°.

[0035] S2, internal parameter solution step.

[0036] The internal calibration model includes 6 parameters: distance to the laser radar, horizontal angle and vertical angle ( r , i, f ) error is calibrated, and the calibration parameter is the corresponding offset value α = ( d ρ , d θ , d φ ), and the distance measurement scale factor s , receiving system horizontal and vertical offset from the device origin h and v Therefore, the calibration parameters are α =( d ρ , d θ , d φ , s , h , v ), the correction equation of the measured value after calibration is:

[0037] For laser radar, each scanner has its own calibration parameters. Therefore, for a 64-line rotating laser radar, the number of internal parameters is 6×64; for micro-electromechanical system solid-state radar, its parameters are similar to those of mechanical type; for array solid-state radar, such as m × n pixels, and the number of its intrinsic parameters is m × n ×6.

[0038] Constructing an internal parameter optimization model: The goal of internal parameter calibration is to minimize the distance between each point on the calibration target plate measured by the laser radar and the target plate plane. That is, when the laser radar scans a plane, the discrete degree of the point cloud on the plane should be minimized. The objective function of the internal parameter optimization model can be defined as: (2) In the above formula, P and Q k The calibration data obtained in the calibration data acquisition process, P is the set of all measured planes, Q k is the set of all points on the plane, d ( q , p k )for Q k midpoint q To plane p k Distance:

[0039] In the above formula, x i , y i , z i For point q The coordinates of the measured values ​​can be expressed in terms of the calibration parameters by applying the correction equations for the measured values. α =( d ρ , d θ , d φ , s , h , v )express.

[0040] The internal parameter solution, whose minimum distance is an optimization problem, can be solved by existing mathematical optimization methods to obtain the optimal solution of the system under the above constraints to determine the optimal value of the calibration parameter. For example, the Levenberg–Marquardt algorithm can be used to use the design parameters as the initial values ​​and obtain the calibration values ​​of the above calibration parameters that meet the constraints through iterative solution.

[0041] Since the above method uses the multi-frame point cloud data as a system for overall iterative solution, it is conducive to achieving global optimization in the laser radar point cloud calibration process and avoiding the problem of local optimization caused by divide and conquer. The conventional method is to obtain the correction value of the data point in the point cloud by the least squares method for each frame of point cloud data, so as to determine the corresponding correction internal parameters of the scanner.

[0042] In the method of the present application, a collection of different frame point cloud data under various preset scenarios within the rated working range of the laser radar 1 is combined to perform an overall solution to achieve global optimization. Obviously, for the same scanner, its correction value may change according to the distance and angle between the laser radar 1 and the reflecting plane 21. In other words, the correction value of the scanning data corresponding to the same scanner in different states may be slightly different. Since the solution of the present application is an overall solution and implicitly utilizes constraints, it can optimize the global parameters of the scanner at the same time to achieve the purpose of obtaining the global optimal solution.

[0043] Optionally, S3, an internal reference verification step is also included.

[0044] Through the integrated control unit 51 and the communication unit 52, the fixed frame carrying the target plate 2 is controlled to move along the guide rail 22 to other positions different from the position when the data is acquired; through the integrated control unit 51 and the communication unit 52, the point cloud data of the target plate 2 at the position scanned by the laser radar 1 to be calibrated is collected; through the integrated control unit 51 and the communication unit 52, the camera array 3 is controlled to solve the plane equation parameters of the target plate 2 relative to the global coordinate system in the current state; the distances from all target plate measurement points to the target plate plane are calculated, and the average distance error is counted; repeat multiple times to determine whether the distance errors of all positions are within an acceptable range, that is, whether they are within a preset threshold. If acceptable, stop calibration; if unacceptable, increase calibration data or re-collect calibration data to recalibrate the internal parameters of the laser radar 1 until the requirements are met.

[0045] The automatic calibration process of the above-mentioned laser radar internal parameter automatic calibration system is as follows: Figure 5 .

[0046] 1. System preparation: First, ensure that the target plate and motion rail, calibration target plate, camera array, calibration platform and gimbal, computing storage unit, communication unit and integrated control unit have been installed and debugged. Check all hardware equipment to ensure that the calibration target plate and the initial position of the lidar are correct.

[0047] 2. System startup: Start the integrated control unit and enter the calibration task process. Start the communication unit to ensure smooth communication between systems.

[0048] 3. Calibration task setting: Set the specific parameters of the calibration task in the integrated control unit, such as calibration task type, calibration accuracy requirements, etc.

[0049] 4. Calibration target plate identification and data collection: Start the target plate motion system, and move the calibration target plate according to the preset task so that it passes through the scanning area of ​​the laser radar. When the target plate stays at each calibration task point in the scanning area of ​​the laser radar 1, the target plate accurately rotates the calibration target plate to the angle required by the instruction according to the instruction requirements of the integrated control unit. The laser radar 1 scans the calibration target plate, collects laser point cloud data, and transmits it to the computing and storage subsystem in real time. The camera arrays distributed on both sides of the motion guide rail can measure the target plate's posture in real time and accurately by identifying and measuring the visual positioning tags fixed on the target plate. The target plate plane equation parameters obtained by the camera array processing are transmitted to the computing and storage unit through the communication unit for the calibration internal parameter solution of the laser radar.

[0050] 5. Data processing and parameter optimization: After receiving the data, the computing storage unit processes the data according to the preset algorithm, identifies the characteristics of the target plate, and calculates the internal calibration parameters of the laser radar. The collected data is optimized with high precision in multiple parameters to ensure the accuracy of the calibration results.

[0051] 6. Calibration result verification: Use the calibration target to verify the calibration result of the LiDAR and check its accuracy and reliability. According to the accuracy setting requirements, adjust the calibration parameters and repeat the above steps until the LiDAR achieves satisfactory calibration accuracy.

[0052] 7. Calibration result storage and report generation: Store the final calibration parameters in the calculation storage unit and generate a detailed calibration report.

[0053] 8. System shutdown and maintenance: After completing the calibration task, shut down all subsystems and perform necessary maintenance work, such as cleaning optical components, checking mechanical parts, etc. Ensure that the system can operate normally the next time it is used.

[0054] The above content is only a description of the preferred implementation of the present invention, and does not limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made by ordinary technicians in this field to the technical solution of the present invention should fall within the protection scope determined by the claims of the present invention.

Claims

1. A laser radar internal parameter calibration method, characterized in that: include: S1. Calibration data acquisition step: obtain multiple frames of point cloud data at different relative positions between the laser radar and the reflection plane of the target plate within the rated working range of the laser radar, where each frame of point cloud data is recorded as pc , the number of point cloud data frames is recorded as q At the same time, corresponding to each frame of point cloud data, the spatial plane equation of the reflection plane 21 is obtained through the camera array 3 n ; For each frame of point cloud data, the calibration data is obtained d =( pc , n ); the calibration data set can be expressed as ; S2. Internal parameter calculation steps: The calibration parameters are α =( δ ρ , δ θ , δ φ , s , h , v ),( δ ρ , δ θ , δ φ ) is the distance, horizontal angle and vertical angle of the laser radar ( ρ , θ , φ ), s is the distance measurement scale factor, h and v To receive the horizontal and vertical offsets of the system from the origin of the device, The correction equation of the calibrated measurement value is: The goal of the internal parameter calibration in the internal parameter optimization model is to minimize the distance between each point on the calibration target plate measured by the lidar and the target plate plane. The objective function of the internal parameter optimization model is defined as: In the formula, P and Q k The calibration data obtained in the calibration data acquisition process, P is the set of all measured planes, Q k is the set of all points on the plane, d ( q , p k )for Q k midpoint q To plane p k Distance: In the above formula, x i , y i , z i For point q The coordinates of the measured values ​​are corrected by the calibration parameters α =( δ ρ , δ θ , δ φ , s , h , v )Sure; The optimal solution of the above system under the constraints is solved by mathematical optimization algorithm to determine the calibration parameters of the lidar α =( δ ρ , δ θ , δ φ , s , h , v ).

2. The laser radar internal parameter calibration method according to claim 1, characterized in that: The S1 calibration data acquisition steps are as follows: S11, adjust the laser radar inclination angle to θ 1; Control the distance between the laser radar and the target plate to the set distance p 1; Collect laser radar θ Scanned at 1 angle p 1 position target plate S Frame point cloud data, denoted as ; Calibration data in the current state , where n1 is the spatial plane equation parameter of the target plate in the current state; S12, repeat S11 step, collect N The target scanning data of the laser radar within the preset distance interval between the target and the target and the spatial plane equation parameters of the corresponding target are combined to form a calibration data set ; S13, repeat steps S11-S12, collect M The target plate scanning data of the laser radar in the preset inclination range and the space plane equation parameters of the corresponding target plate are combined to form a complete calibration data set Q = .

3. The laser radar internal parameter calibration method according to claim 2, characterized in that: In the step S1 of obtaining calibration data, the space plane equation parameters of the target plate in the current state are obtained by solving the images obtained by imaging the reflection plane respectively by several cameras in the camera array at this time.

4. The laser radar internal parameter calibration method according to claim 2, characterized in that: The preset distance interval is 0.5-50m, and / or the preset inclination angle interval is -45-45°.

5. The laser radar internal parameter calibration method according to claim 2, characterized in that: The mathematical optimization algorithm in the S2 internal parameter solution step is the Levenberg-Marquardt algorithm.

6. The laser radar internal parameter calibration method according to claim 1, characterized in that: After the S2 internal parameter solution step is completed, the S3 internal parameter verification step is also executed: the relative position change between the target plate and the laser radar is controlled, and multiple frames of point cloud data corresponding to the reflection plane corrected by the calibration parameters are obtained. At the same time, the spatial plane equation of the reflection plane is obtained for each frame of point cloud data, and the average error of the point cloud data to the corresponding spatial plane equation is counted.

7. The laser radar internal parameter calibration method according to claim 6, characterized in that: If the average error is outside the threshold range, repeat the calibration data acquisition step S1 and the internal parameter solution step S2 to perform recalibration until the average error is within the threshold range.

8. A laser radar internal parameter calibration system, characterized in that: include A laser radar (1), which has a fixed position; A target plate (2) having a varying spatial distance relative to the laser radar 1; and a reflecting plane (21) having a limited area; The camera array (3) includes a plurality of cameras (31), wherein the cameras (31) are used to combine and determine the spatial plane equation of the reflection plane (21).

9. The laser radar internal parameter calibration system according to claim 8, characterized in that: The laser radar (1) can rotate around a fixed point in space, or the reflection plane (21) can rotate around a fixed point in space.

10. The laser radar internal parameter calibration system according to claim 8, characterized in that: The target plate (2) is movably arranged on a guide rail (22) via a fixing frame (23); the guide rail (22) extends in a direction away from the laser radar (1). Or, the target plate (2) is arranged on a fixed frame (23) in a controlled rotational manner, Alternatively, the target plate (2) is movably arranged on the guide rail (22) via a fixing frame (23); the guide rail (22) extends in a direction away from the laser radar (1); the cameras (31) in the camera array (3) are divided into two groups, the two groups of cameras (31) are respectively arranged on both sides of the guide rail (22), and the cameras (31) in each group are arranged in sequence and spaced apart along the extension direction of the guide rail (22).

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