Systems, methods, and machine-readable storage media for multi-sensor calibration parameter

Abstract

The application provides a multi-sensor calibration parameter system, method and machine readable storage medium. The multi-sensor calibration parameter method comprises the following steps: establishing a first coordinate system by a total station, and obtaining coordinate values of a plurality of sensors; converting the first coordinate system into a second coordinate system with an inertial navigation as an origin; calculating a rod arm value between the sensors and the inertial navigation in the second coordinate system; calculating L2I calibration parameters according to the rod arm value; calculating camera intrinsic parameters; calculating L2C calibration parameters according to the camera intrinsic parameters; calculating C2I calibration parameters according to the L2I calibration parameters and the L2C calibration parameters; calculating main and auxiliary laser radar calibration parameters according to main and auxiliary laser point clouds; and calculating calibration parameters between the auxiliary laser radar and the inertial navigation according to the L2I calibration parameters and the main and auxiliary laser radar calibration parameters. According to the scheme, the calibration parameters between the sensors are calculated, the road information collected by a subsequent information collection vehicle is integrated in a unified coordinate system, and map production and quality inspection are performed.

Description

Technical Field

[0001] This invention relates to the fields of map navigation and autonomous driving, and in particular to a system, method, and machine-readable storage medium for calibrating parameters of multiple sensors. Background Technology

[0002] In the fields of map navigation and autonomous driving, information collection vehicles collect road information during driving through multiple sensors, such as LiDAR, cameras, GNSS antennas, and inertial navigation systems (INS). After the system collects information, each sensor records the information with itself as the coordinate origin. Therefore, all information needs to be fused into a unified coordinate system for processing. However, the actual sensor positions on each information collection vehicle may vary. Therefore, after the sensors are installed on each information collection vehicle, it is necessary to fuse the different sensors into the same coordinate system to determine the relative positional relationships between the different sensors. Summary of the Invention

[0003] One objective of this invention is to fuse the positions of different sensors into the same inertial navigation coordinate system.

[0004] A further objective of this invention is to calibrate the relative positional relationships between different sensors.

[0005] Another objective of this invention is to integrate the road information collected by the information collection vehicle into a unified coordinate system.

[0006] In particular, the present invention provides a multi-sensor calibration system, comprising:

[0007] The information collection vehicle is equipped with multiple sensors, including lidar, inertial navigation, GNSS antenna and camera. Each sensor can record and collect surrounding data in its own coordinate system.

[0008] A calibration device for fusing the relative positional relationships of sensors into a single inertial navigation coordinate system, comprising:

[0009] The lever arm value measurement and calculation module is used to calculate the lever arm value from the GNSS antenna and lidar to the center of the inertial navigation coordinate system.

[0010] The L2I calibration module is used to calibrate the relative positional relationship between the lidar and the inertial navigation system.

[0011] The camera intrinsic parameter calibration module is used to determine the specific parameter configuration of the camera's internal parameters;

[0012] The L2C calibration module is used to calibrate the relative positional relationship between the main lidar and the camera;

[0013] The C2I calibration module is used to calibrate the relative positional relationship between the camera and the inertial navigation system.

[0014] The main and secondary lidar calibration module is used to calibrate the relative positional relationship between the main lidar and the secondary lidar.

[0015] The secondary lidar and inertial navigation calibration module is used to calibrate the relative positional relationship between the secondary lidar and the inertial navigation system.

[0016] Optionally, the lever arm value measurement and calculation module is also configured to:

[0017] A first coordinate system with the total station as the origin is established using a total station, and the coordinate values ​​of multiple sensors are obtained. These sensors include: lidar, inertial navigation, GNSS antenna, and camera. The coordinate values ​​include the first coordinate value of the lidar, the second coordinate value of the inertial navigation, the third coordinate value of the GNSS antenna, and the fourth coordinate value of the camera. The coordinate values ​​also include the X, Y, and Z values ​​of the sensors in the first coordinate system.

[0018] The first coordinate system is transformed into a second coordinate system with the inertial navigation system as the origin. The second coordinate system records the target coordinate values ​​generated after the coordinate values ​​are transformed in the second coordinate system. The target coordinate values ​​include the first target coordinate values ​​of the lidar, the second target coordinate values ​​of the inertial navigation system, the third target coordinate values ​​of the GNSS antenna, and the fourth target coordinate values ​​of the camera. The target coordinate values ​​include the X, Y, and Z values ​​of various sensors in the second coordinate system.

[0019] Calculate the lever arm value between one or more of the target coordinates (first target, second target, third target, and fourth target) and the inertial navigation coordinates, where the inertial navigation coordinates are the origin of the second coordinate system.

[0020] Optionally, the L2I calibration module is also configured to: collect route information, convert the route information and the boom value of the GNSS antenna into a coordinate trajectory information file; and convert the coordinate trajectory information file and the boom value of the lidar into L2I calibration parameters.

[0021] The camera intrinsic parameter calibration module is also configured to: acquire calibration board photos generated by the camera; import the calibration board photos into a preset tool to calculate the camera intrinsic parameters, which include: camera focal length, principal point coordinates, radial distortion, tangential distortion, and reprojection error;

[0022] The L2C calibration module is also configured to: obtain the camera's intrinsic parameters; fill in the configuration file based on the camera's intrinsic parameters; and import the photos, laser point clouds, and configuration file into a preset calibration program to calculate the L2C calibration parameters.

[0023] The C2I calibration module is also configured to: acquire L2C calibration parameters; import the L2I and L2C calibration parameters into a preset program software, and generate C2I calibration parameters using a preset formula; and

[0024] The preset formula includes: C2I=L2I×L2C^(-1).

[0025] Optionally, the main and secondary lidar calibration module is also configured to: collect the main lidar and secondary lidar point clouds generated by the main lidar and secondary lidar facing the same scene at the same time; import the main lidar point clouds and secondary lidar point clouds into a preset calibration program for calculation to obtain the main and secondary lidar calibration parameters;

[0026] The secondary lidar and inertial navigation calibration module is also configured to import L2I calibration parameters and primary and secondary lidar calibration parameters into a preset calibration program for calculation to obtain the calibration parameters between the secondary lidar and the inertial navigation system.

[0027] According to another aspect of the present invention, a method for calibrating parameters of multiple sensors is also provided, comprising:

[0028] A first coordinate system with the total station as the origin is established using a total station, and the coordinate values ​​of multiple sensors are obtained. These sensors include: lidar, inertial navigation, GNSS antenna, and camera. The coordinate values ​​include the first coordinate value of the lidar, the second coordinate value of the inertial navigation, the third coordinate value of the GNSS antenna, and the fourth coordinate value of the camera. The coordinate values ​​also include the X, Y, and Z values ​​of the sensors in the first coordinate system.

[0029] The first coordinate system is transformed into a second coordinate system with the inertial navigation system as the origin. The second coordinate system records the target coordinate values ​​generated after the coordinate values ​​are transformed in the second coordinate system. The target coordinate values ​​include the first target coordinate values ​​of the lidar, the second target coordinate values ​​of the inertial navigation system, the third target coordinate values ​​of the GNSS antenna, and the fourth target coordinate values ​​of the camera. The target coordinate values ​​include the X, Y, and Z values ​​of various sensors in the second coordinate system.

[0030] Calculate the lever arm value between one or more of the target coordinates (first target, second target, third target, and fourth target) and the inertial navigation coordinates, where the inertial navigation coordinates are the origin of the second coordinate system.

[0031] The L2I calibration parameters are calculated based on the lever arm value. The L2I calibration parameters are used to calibrate the relative positional relationship between the lidar and the inertial navigation system.

[0032] The camera's intrinsic parameters are calculated based on the data collected by the camera.

[0033] The L2C calibration parameters are calculated based on the camera's intrinsic parameters. The L2C calibration parameters are used to calibrate the relative positional relationship between the main lidar and the camera.

[0034] The C2I calibration parameters are calculated based on the L2I and L2C calibration parameters. The C2I calibration parameters are used to calibrate the relative positional relationship between the camera and the inertial navigation system.

[0035] Collect the main laser point cloud and the secondary laser point cloud generated by the main lidar and the secondary lidar facing the same scene at the same time;

[0036] The main laser point cloud and the secondary laser point cloud are imported into the first preset calibration program for calculation to obtain the calibration parameters of the main and secondary lidars. The calibration parameters of the main and secondary lidars are used to calibrate the relative positional relationship between the main lidar and the secondary lidar.

[0037] The L2I calibration parameters and the calibration parameters of the main and secondary lidars are imported into the second preset calibration program for calculation to obtain the calibration parameters between the secondary lidar and the inertial navigation system. The calibration parameters between the secondary lidar and the inertial navigation system are used to calibrate the relative positional relationship between the secondary lidar and the secondary inertial navigation system.

[0038] Optionally, the first coordinate system and the second coordinate system also include: the front wheel point and the rear wheel point of the information collection vehicle;

[0039] The steps to convert the first coordinate system to a second coordinate system with the inertial navigation system as the origin include:

[0040] Import the first coordinate system into the preset program;

[0041] Connect the front wheel point and the rear wheel point in the first coordinate system;

[0042] Draw a perpendicular line along the rear wheel and measure the angle between the line and the perpendicular line;

[0043] Rotate all measurement points in the first coordinate system along the connecting line with the rear wheel point as the center until they coincide with the vertical line;

[0044] Redefine the coordinate axes in the first coordinate system, and generate a second coordinate system with the inertial navigation point as the origin. The vertical line is the positive direction of the Y-axis, and the right vertical line is the positive direction of the X-axis.

[0045] Calculate the coordinates of each point of multiple sensors in the second coordinate system and the Z value to generate the first target coordinate value, the second target coordinate value, the third target coordinate value and the fourth target coordinate value.

[0046] Optionally, the step of calculating the lever arm value from the sensor to the center of the inertial navigation coordinate system based on the first coordinate includes:

[0047] The first azimuth angle from the rear wheel to the front wheel and the second azimuth angle from the inertial navigation system to each measurement point in the first coordinate system are calculated using the azimuth angle calculation formula.

[0048] The straight-line distance from the inertial navigation system to the measurement point is calculated using the following formula:

[0049] , where △X 2 惯导→测量点 The square of the X-axis distance from the inertial navigation system to the measurement point is represented by ΔY. 2 惯导→测量点 This represents the square of the Y-axis distance from the inertial navigation system to the measurement point;

[0050] The azimuth difference Δα1 is obtained by subtracting the first azimuth from the second azimuth.

[0051] Using the inertial navigation system's coordinate system as the origin, i.e., X... 惯导 =0, Y 惯导 =0; Calculate the coordinates of the measurement point using the following formula:

[0052] X 测量点 =X 惯导 +S 惯导→测量点 *sin△α1;

[0053] Y 测量点 =Y 惯导 +S 惯导→测量点 *cos△α1;

[0054] Z 测量点 =Z 测量点中心 -Z 惯导坐标轴中心 ;

[0055] Among them, X 测量点、 Y 测量点 and Z 测量点 S represents the coordinates of the measured point in a coordinate system with the inertial navigation system's coordinates as the origin. 惯导→测量点 This represents the straight-line distance from the inertial navigation system to the measurement point.

[0056] Optionally, the steps for calculating the camera's intrinsic parameters using data collected by the camera include:

[0057] Acquire the calibration board image generated by the camera;

[0058] Import the calibration board photos into the preset tools to calculate the camera's intrinsic parameters;

[0059] The camera intrinsic parameters include: camera focal length, principal point coordinates, radial distortion, tangential distortion, and reprojection error.

[0060] Optionally, the steps for calculating the L2C calibration parameters based on the camera's intrinsic parameters include:

[0061] The calibration board data, including photographs and laser point clouds, is collected by a camera and a lidar to capture a preset number of calibration board data at different positions, heights, and rotational angles.

[0062] Obtain the camera's intrinsic parameters;

[0063] Fill in the configuration file according to the camera's intrinsic parameters;

[0064] Import the photos, laser point clouds, and configuration files into the preset calibration program to calculate the L2C calibration parameters.

[0065] Optionally, the steps for calculating the C2I calibration parameters based on the L2I calibration parameters and the L2C calibration parameters include:

[0066] Import the L2I calibration parameters and L2C calibration parameters into the preset program software, and generate the C2I calibration parameters through the preset formula;

[0067] The preset formula includes: C2I=L2I×L2C^(-1).

[0068] According to another aspect of the present invention, a machine-readable storage medium is also provided, on which a machine-executable program is stored, wherein the machine-executable program, when executed by a processor, implements the method for multi-sensor calibration parameters as described above.

[0069] According to another aspect of the present invention, a computer device is also provided, including a memory, a processor, and a machine-executable program stored in the memory and running on the processor, wherein the processor executes the machine-executable program to implement the method of multi-sensor calibration parameters as described above.

[0070] In this invention, a first coordinate system is established with the total station as the origin, and coordinate values ​​from multiple sensors are acquired. These coordinate values ​​include the first coordinate value from the lidar, the second coordinate value from the inertial navigation system (INS), the third coordinate value from the GNSS antenna, and the fourth coordinate value from the camera. The first coordinate system is then converted into a second coordinate system with the INS as the origin. The second coordinate system records the target coordinate values ​​generated after the conversion. These target coordinate values ​​include the first target coordinate value from the lidar, the second target coordinate value from the INS, the third target coordinate value from the GNSS antenna, and the fourth target coordinate value from the camera. The lever arm value between one or more of the first, second, third, and fourth target coordinate values ​​and the INS coordinate value is calculated. The data is then compared with the route information collected by the information acquisition vehicle and the lever arm value of the sensors. The L2I calibration parameters are calculated; the camera intrinsic parameters are calculated based on the calibration board photos generated by the camera; a preset number of calibration board data with different positions, heights, and rotation angles are collected by the camera and LiDAR, and the L2C calibration parameters are calculated based on the calibration board data and the camera intrinsic parameters; the L2I and L2C calibration parameters are imported into a preset program software, and the C2I calibration parameters are generated through a preset conversion formula; the main and secondary LiDAR point clouds generated by the main and secondary LiDARs facing the same scene at the same time are collected; the main and secondary LiDAR point clouds are imported into the first preset calibration program for calculation to obtain the main and secondary LiDAR calibration parameters; the L2I calibration parameters and the main and secondary LiDAR calibration parameters are imported into the second preset calibration program for calculation to obtain the calibration parameters between the secondary LiDAR and the inertial navigation system. This method enables the determination of the positional relationship between multiple sensors and the inertial navigation system on the information collection vehicle through calibration parameters, and integrates the relative positional relationships between different sensors into the same inertial navigation coordinate system. This facilitates the subsequent integration of road information collected by the information collection vehicle into a unified coordinate system, thereby enabling map production and quality inspection.

[0071] The above and other objects, advantages and features of the present invention will become more apparent to those skilled in the art from the following detailed description of specific embodiments of the invention in conjunction with the accompanying drawings. Attached Figure Description

[0072] The following sections will describe some specific embodiments of the invention in detail by way of example and not limitation, with reference to the accompanying drawings. The same reference numerals in the drawings denote the same or similar parts or portions. Those skilled in the art should understand that these drawings are not necessarily drawn to scale. In the drawings:

[0073] Figure 1 This is a schematic diagram showing the positions and coordinate axes of multiple sensors in a vehicle according to an embodiment of the present invention;

[0074] Figure 2This is a schematic diagram showing the installation positions of multiple sensors on an information acquisition vehicle in a method for calibrating parameters of multiple sensors according to an embodiment of the present invention.

[0075] Figure 3 It is a total station measurement Figure 2 A schematic diagram showing the installation location of the sensor when displaying sensor information;

[0076] Figure 4 This is a schematic diagram of the architecture of a multi-sensor calibration system according to an embodiment of the present invention;

[0077] Figure 5 This is a flowchart illustrating a method for calibrating parameters of multiple sensors according to an embodiment of the present invention;

[0078] Figure 6 This is a schematic diagram of the total station coordinates after being imported into computer-aided design software according to a method for multi-sensor calibration parameters according to an embodiment of the present invention.

[0079] Figure 7 yes Figure 6 A coordinate diagram transformed by computer-aided design software;

[0080] Figure 8 This is a schematic diagram of a machine-readable storage medium in a method for calibrating multi-sensor parameters according to an embodiment of the present invention; and

[0081] Figure 9 This is a schematic diagram of a computer device in a method for calibrating parameters of multiple sensors according to an embodiment of the present invention. Detailed Implementation

[0082] Those skilled in the art should understand that the embodiments described below are merely a part of the embodiments of the present invention, and not all of the embodiments of the present invention. These partial embodiments are intended to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention. Based on the embodiments provided by the present invention, all other embodiments obtained by those skilled in the art without creative effort should still fall within the scope of protection of the present invention.

[0083] Figure 1 This is a schematic diagram of multiple sensor coordinate axes according to an embodiment of the present invention. 11, 12, and 13 represent cameras, and one possible example of their coordinate axes is: the X-axis points to the right along the vehicle's direction of travel, the Y-axis points directly above the vehicle, and the Z-axis represents the camera's own position, aligned with the vehicle's direction of travel.

[0084] 14 represents a lidar system, with possible coordinate axes such as the X-axis pointing to the left along the vehicle's direction of travel, the Y-axis either in the same direction or opposite to the vehicle's direction of travel, and the Z-axis pointing directly above the vehicle; 15 represents an inertial navigation system, with possible coordinate axes such as the X-axis pointing to the right along the vehicle's direction of travel, the Y-axis either in the same direction or opposite to the vehicle's direction of travel, and the Z-axis pointing directly above the vehicle.

[0085] It should be noted that those skilled in the art can set the coordinate system for each sensor according to the actual situation. Figure 1 This is just one example.

[0086] Since multiple sensors each have their own coordinate system, during the statistical data collection process, it is necessary to unify the coordinate values ​​of multiple sensors into a single coordinate system. Therefore, this method proposes a way to fuse the coordinates of multiple sensors into the same inertial navigation coordinate system, which is also a method to calibrate the positional relationship of different sensors relative to the inertial navigation system.

[0087] Figure 2 This is a schematic diagram showing the installation positions of multiple sensors on an information acquisition vehicle in a method for calibrating parameters of multiple sensors according to an embodiment of the present invention.

[0088] Figure 3 It is a total station measurement Figure 2 The diagram shows the installation location of the sensor when the sensor information is displayed. The total station is a total station electronic distance measuring instrument, a high-tech surveying instrument integrating optics, mechanics, and electronics. It is a surveying instrument system that integrates horizontal angle, vertical angle, distance (slope distance, horizontal distance), and elevation difference measurement functions. It should be noted that... Figure 3 The location for setting up the total station is just one specific example. When setting up the total station, first find a location that allows for observation of as many sensor reference points as possible, set up the instrument, and level it, ensuring the leveling error is less than 10″. Then, enter the operation interface, freely set up the station at that location, and then perform coordinate measurements at any point, saving the coordinates of each point. The measurement points are the center of the inertial navigation coordinate axis, the center of the main laser coordinate axis, the antenna phase center, and the same side of the front and rear wheels.

[0089] Figure 4 This is a schematic diagram of the architecture of a multi-sensor calibration system according to an embodiment of the present invention. The multi-sensor calibration system may include an information collection vehicle 410 and a calibration device 420. The information collection vehicle 410 may be a vehicle or other mobile data collection device equipped with multiple sensors, including devices such as lidar, inertial navigation, GNSS antenna, and cameras. All of the above sensors are capable of recording and collecting surrounding data in their own coordinate system.

[0090] The calibration device 420 can calibrate the positional relationship between multiple sensors by using data collected by multiple sensors in the information collection vehicle 410, thereby integrating the data collected by multiple sensors into a unified coordinate system, thus preparing for the subsequent production and quality inspection of high-precision maps.

[0091] The calibration device 420 may include: a lever arm value measurement and calculation module 421, an L2I calibration module 422, a camera intrinsic parameter calibration module 423, an L2C calibration module 424, a C2I calibration module 425, a main and secondary lidar calibration module 426, and a secondary lidar and inertial navigation calibration module 427.

[0092] The lever arm value measurement and calculation module 421 is used to measure and calculate the lever arm value from the sensor to the target position. A first coordinate system is established with the total station as the origin, and the coordinate values ​​of multiple sensors are acquired. These sensors include a lidar, an inertial navigation system, a GNSS antenna, and a camera. The coordinate values ​​include the first coordinate value of the lidar, the second coordinate value of the inertial navigation system, the third coordinate value of the GNSS antenna, and the fourth coordinate value of the camera. The coordinate values ​​also include the X, Y, and Z values ​​of the sensors in the first coordinate system.

[0093] The first coordinate system is transformed into a second coordinate system with the inertial navigation system as the origin. The second coordinate system records the target coordinate values ​​generated after the coordinate values ​​are transformed in the second coordinate system. The target coordinate values ​​include the first target coordinate values ​​of the lidar, the second target coordinate values ​​of the inertial navigation system, the third target coordinate values ​​of the GNSS antenna, and the fourth target coordinate values ​​of the camera. The target coordinate values ​​include the X, Y, and Z values ​​of various sensors in the second coordinate system.

[0094] Calculate the lever arm value between one or more of the target coordinates (first target, second target, third target, and fourth target) and the inertial navigation coordinates, where the inertial navigation coordinates are the origin of the second coordinate system.

[0095] The L2I calibration module 422 is used to calibrate the relative positional relationship between the lidar and the inertial navigation system. Selected route information is collected by the information acquisition vehicle, and the route information, along with the GNSS antenna boom value calculated by the boom value measurement and calculation module 421, is converted into a coordinate trajectory information file. Subsequently, the coordinate trajectory information file and the lidar boom value are converted into L2I calibration parameters.

[0096] The camera intrinsic parameter calibration module 423 is used to determine the specific internal parameter configuration of the camera. It takes pictures of a calibration board at a preset location using a camera installed on the information acquisition vehicle, and obtains the specific intrinsic parameters of each camera based on the captured images. One optional implementation of this module is to import the calibration board images into a preset tool to calculate the camera intrinsic parameters. A specific example of a preset tool is the CameraCalibrator tool in MATLAB. The camera intrinsic parameters include: camera focal length, principal point coordinates, radial distortion, tangential distortion, and reprojection error.

[0097] The L2C calibration module 424 is used to calibrate the relative positional relationship between the main LiDAR and the camera. It collects a preset number of calibration board data from the camera and LiDAR installed on the information acquisition vehicle. The calibration board data may include photographs and laser point clouds. Then, L2C calibration parameters are calculated based on the camera intrinsic parameters obtained from the camera intrinsic parameter calibration module 423 and the calibration board data. An optional implementation of this module includes: filling a configuration file with the camera intrinsic parameters obtained from the camera intrinsic parameter calibration module 423; and importing the photographs, laser point clouds, and the aforementioned configuration file from the calibration board data into a preset calibration program to calculate the L2C calibration parameters.

[0098] The C2I calibration module 425 is used to calibrate the relative positional relationship between the camera and the inertial navigation system. It calculates the C2I calibration parameters using the L2I calibration parameters obtained from the L2I calibration module 422 and the L2C calibration parameters obtained from the L2C calibration module 424. An optional implementation of this module is as follows: the L2I and L2C calibration parameters are imported into MATLAB software and converted using preset formulas to obtain the C2I calibration parameters.

[0099] The main and secondary lidar calibration module 426, also known as the L2L (secondary) calibration module, is used to calibrate the relative positional relationship between the main lidar and the secondary lidar. It collects the main and secondary lidar point clouds generated at the same time and facing the same scene by the main and secondary lidars installed on the information collection vehicle. The main and secondary lidar point clouds are then imported into a preset calibration program for calculation to obtain the L2L (secondary) calibration parameters.

[0100] The secondary lidar and inertial navigation calibration module 427, also known as the L(secondary)2I calibration module, calculates the L(secondary)2I calibration parameters using the L2I calibration parameters obtained from the L2I calibration module 422 and the L2L(secondary) calibration parameters obtained from the primary and secondary lidar calibration modules 426.

[0101] After processing by the multi-sensor calibration system, L2I calibration parameters, C2I calibration parameters, and L(sub)2I calibration parameters can be calculated based on the data collected by the sensors on each information collection vehicle. This determines the relative positional relationship between the main LiDAR, camera, and sub LiDAR relative to the inertial navigation system. As a result, when the main LiDAR, camera, and sub LiDAR collect data in the future, the data can be converted into a coordinate system with the inertial navigation system as the origin based on the above calibration parameters, and finally, high-precision maps can be produced and quality inspected.

[0102] Figure 5 This is a flowchart illustrating a method for calibrating parameters using multiple sensors according to an embodiment of the present invention. The process may include:

[0103] Step S501: Establish a first coordinate system with the total station as the origin using a total station, and acquire the coordinate values ​​of multiple sensors. These multiple sensors may include: a lidar, an inertial navigation system, a GNSS antenna, and a camera. The coordinate values ​​may include the first coordinate value of the lidar, the second coordinate value of the inertial navigation system, the third coordinate value of the GNSS antenna, and the fourth coordinate value of the camera. Furthermore, these coordinate values ​​include the X, Y, and Z values ​​of the corresponding sensors in the first coordinate system.

[0104] It should be noted that when using a total station for measurement, first find a location that allows for observation of as many sensor reference points as possible, set up the instrument, and level it, ensuring the leveling error is less than 10″. Then, enter the work interface, freely set up the station at that location, and perform coordinate measurements at any point, saving the coordinates of each point. Measurement points include the center of the inertial navigation coordinate axis, the center of the main laser coordinate axis, the antenna phase center, and the same side of the front and rear wheels.

[0105] Step S502: Convert the first coordinate system into a second coordinate system with the inertial navigation system as the origin. The second coordinate system records the target coordinate values ​​generated after the coordinate values ​​are converted in the second coordinate system. The target coordinate values ​​include the first target coordinate values ​​of the lidar, the second target coordinate values ​​of the inertial navigation system, the third target coordinate values ​​of the GNSS antenna, and the fourth target coordinate values ​​of the camera. The target coordinate values ​​include the X, Y, and Z values ​​of various sensors in the second coordinate system.

[0106] In some embodiments of this step, the calculation method can be a graphical method. The steps of the graphical method may include: summarizing the coordinate values ​​of multiple sensors measured in step S501 into a table; swapping the X and Y coordinates of the table data and importing it into computer-aided design software. The purpose of swapping the X and Y coordinates here is to convert the surveying coordinate system generated by the total station into the mathematical coordinate system in the computer-aided design software; connecting the front wheel point and the rear wheel point in the computer-aided design software; drawing a vertical line along the rear wheel and measuring the angle between the connecting line and the vertical line; rotating all measurement points along the connecting line with the rear wheel point as the center until they coincide with the vertical line; redefining the coordinate axes, generating a second coordinate system with the inertial navigation point as the origin, the vertical line as the positive direction of the Y axis, and the right vertical line as the positive direction of the X axis; calculating the coordinates of each point of multiple sensors and the Z value in the second coordinate system to generate the first target coordinate value, the second target coordinate value, the third target coordinate value, and the fourth target coordinate value.

[0107] One example of computer-aided design software is CAD. Those skilled in the art can choose the computer-aided design software to use based on the actual situation. Figure 6 This is a schematic diagram of the total station coordinates after being imported into computer-aided design software according to a method for multi-sensor calibration parameters according to an embodiment of the present invention; the schematic diagram shows the positions of the inertial navigation system, lidar, antenna, and the front and rear wheels of the vehicle in a mathematical coordinate system.

[0108] Figure 7 yes Figure 8 A coordinate diagram after conversion by computer-aided design software.

[0109] In other embodiments of this step, the calculation method can be a tabular calculation method. The steps of the tabular calculation method may include: calculating the first azimuth angle from the rear wheel to the front wheel in the first coordinate system and the second azimuth angle from the inertial navigation system to each measurement point in the first coordinate system using the azimuth angle calculation formula; wherein, a specific application example of the azimuth angle calculation formula is as follows:

[0110] α 后轮→前轮 =O→rear wheel azimuth angle +∠Orear wheel to front wheel ±180°. This formula is used to calculate the azimuth angle from the rear wheel to the front wheel.

[0111] An example of its application is the second azimuth angle from the inertial navigation system to each measurement point in the first coordinate system:

[0112] The formula for calculating the azimuth angle from the inertial navigation system to GNSS1 (antenna 1) is as follows:

[0113] α 惯导→GNSS1 =O1→Inertial Navigation Azimuth Angle +∠O1Inertial Navigation GNSS1±180°; where O1 is the front of the inertial navigation system and is parallel to the line connecting O→rear wheel.

[0114] The straight-line distance from the inertial navigation system to each measurement point is then calculated using the following formula:

[0115] , where △X 2 惯导→测量点 The square of the X-axis distance from the inertial navigation system to the measurement point is represented by ΔY. 2 惯导→测量点 This represents the square of the Y-axis distance from the inertial navigation system to the measurement point; the azimuth difference Δα1 is obtained by subtracting the first azimuth angle from the second azimuth angle; the origin is the coordinate system of the inertial navigation system, i.e., X... 惯导 =0, Y 惯导 =0; Calculate the coordinates of the measurement point using the following formula:

[0116] X 测量点 =X 惯导 +S 惯导→测量点 *sin△α1;

[0117] Y 测量点 =Y 惯导 +S 惯导→测量点 *cos△α1;

[0118] Z 测量点 =Z 测量点中心 -Z 惯导坐标轴中心 ;

[0119] Among them, X 测量点、 Y 测量点 and Z 测量点 S represents the coordinates of the measured point in a coordinate system with the inertial navigation system's coordinates as the origin. 惯导→测量点 This represents the straight-line distance from the inertial navigation system to the measurement point.

[0120] Step S503: Calculate the lever arm value between one or more of the target coordinate values ​​(first target coordinate value, second target coordinate value, third target coordinate value, and fourth target coordinate value) and the inertial navigation coordinate value. The inertial navigation coordinate value is the origin of the second coordinate system.

[0121] Step S504: Calculate the L2I calibration parameters based on the boom arm values. This step includes: acquiring the route information collected by the information acquisition vehicle, converting the route information and the boom arm values ​​of the GNSS antenna into a coordinate trajectory information file, and converting the coordinate trajectory information file and the boom arm values ​​of the lidar into L2I calibration parameters.

[0122] One implementation of route information collection is as follows: Select a number of 90° turns or more, where there must be flat, block-shaped objects such as flat building walls or signs at the turns; ensure strong GPS satellite information along the route and avoid signal obstruction scenarios such as tunnels or under overpasses; one example of the preset number is 20, which can reduce resource consumption without affecting data accuracy.

[0123] Some implementations of converting route information and GNSS antenna boom values ​​into coordinate trajectory information files include: performing trajectory calculation on the collected project .gps file, inputting the antenna boom values ​​generated in step S503 as a configuration file into the model calculation program; and outputting the result .nav trajectory file.

[0124] The coordinate trajectory information file and the LiDAR arm values ​​are converted into L2I calibration parameters. Some implementations include: using a preset calibration program for calibration calculation; inputting the main laser arm values ​​generated in step S503 as a configuration file into the preset calibration program, associating them with the .nav trajectory file, and then performing calculation; finally, the L2I calibration parameters are output.

[0125] The L2I calibration parameters are in the format of a 4x4 matrix. A specific example of a 4x4 matrix is ​​shown in Table 1.

[0126] Table 1

[0127] -0.998112 -0.061413 -0.000595 -0.005000 0.061408 -0.998091 -0.006532 1.123000 0.000995 -0.006483 0.999978 1.388000 0.000000 0.000000 0.000000 1.000000

[0128] The 3x3 numbers in the matrix record the rotation angle of the main laser relative to the inertial navigation system on the X, Y, and Z axes. The fourth column records the lever arm value of the main laser, and the numbers in the fourth row represent the identity matrix. It should be noted that those skilled in the art can set the representation of the L2I calibration parameters according to the actual situation.

[0129] Step S505: Calculate the camera's intrinsic parameters using the data collected by the camera. This step includes: acquiring a calibration board image generated by the camera; importing the calibration board image into a preset tool to calculate the camera's intrinsic parameters. A specific example of a preset tool is the CameraCalibrator tool in MATLAB. The camera's intrinsic parameters include: camera focal length, principal point coordinates, radial distortion, tangential distortion, and reprojection error.

[0130] It should be noted that the following requirements must be observed during the acquisition of calibration board photos:

[0131] 1. Take photos of the calibration board from different angles using a camera. The angle between the calibration board and the camera plane should not exceed 70°. Avoid excessively large angles, as this will blur the crosshairs on the black and white board and prevent the program from recognizing them.

[0132] 2. The calibration board to be photographed must have its entire black and white frame within the camera's field of view, with no obstructions in the middle;

[0133] 3. The calibration board should be centered in the camera's field of view, maximizing the size of the checkerboard within the camera's field of view;

[0134] 4. The four corners and four sides of the photo are covered by calibration plates.

[0135] Step S506: Calculate the L2C calibration parameters based on the camera's intrinsic parameters. This step includes: collecting a preset number of calibration board data using the camera and LiDAR installed on the information collection vehicle; the calibration board data may include photos and LiDAR point clouds; filling in the configuration file based on the camera's intrinsic parameters; and importing the photos, LiDAR point clouds, and configuration file into a preset calibration program to calculate the L2C calibration parameters.

[0136] The following requirements should be noted during the data acquisition process from the calibration board:

[0137] 1. The calibration board is positioned at different distances from the camera and lidar, both in front, behind, left, and right.

[0138] 2. The calibration plate is rotated at different heights and angles at different locations;

[0139] 3. Data is collected when the camera, lidar, and calibration board are all relatively stationary.

[0140] 4. Collect a preset number of data points at different positions, heights, and rotational angles in a balanced manner. One possible example of the preset number is 69. Practical verification has shown that collecting 69 data points can maintain data accuracy while reducing resource consumption.

[0141] Step S507: Calculate the C2I calibration parameters based on the L2I and L2C calibration parameters. Import the L2I calibration parameters obtained in step S504 and the L2C calibration parameters obtained in step S506 into the preset program software, and generate the C2I calibration parameters using a preset formula.

[0142] An optional example of the preset formula is: C2I=L2I×L2C^(-1), where L2I represents the L2I parameter matrix generated in step S504, and L2C represents the L2C parameter matrix generated in step S506.

[0143] Step S508: Acquire the main laser point cloud and the secondary laser point cloud generated by the main lidar and the secondary lidar facing the same scene at the same time. The following requirements must be observed during the process of acquiring the main laser point cloud and the secondary laser point cloud generated by the main lidar and the secondary lidar facing the same scene at the same time:

[0144] 1. A secluded road section with no vehicles or pedestrians, including auxiliary roads with no more than four lanes, and no median strip. There are numerous streetlights, tree trunks, and other pole-like objects on both sides.

[0145] 2. During the data collection process, it is essential to ensure that there are virtually no vehicles, electric vehicles, or pedestrians passing by, and to avoid easily disturbing factors such as bushes or dense foliage.

[0146] 3. During the data collection process, move in an S-shape, stand still on one side of the road for 15 seconds before starting and changing positions.

[0147] This requirement enables the accurate acquisition of laser point clouds generated when the primary and secondary lasers face the same object, while avoiding other interfering factors.

[0148] Step S509: Import the main laser point cloud and the secondary laser point cloud into the first preset calibration program for calculation to obtain the calibration parameters of the main and secondary lidar.

[0149] Step S510: Import the L2I calibration parameters and the main and secondary lidar calibration parameters into the second preset calibration program for calculation to obtain the calibration parameters between the secondary lidar and the inertial navigation system.

[0150] This method ultimately yields L2I calibration parameters, C2I calibration parameters, and L(sub)2I calibration parameters, determining the relative positional relationships between the primary and secondary lidars, the camera, and the inertial navigation system. This integrates the relative positional relationships between different sensors into the same inertial navigation coordinate system, facilitating the subsequent integration of road information collected by data acquisition vehicles into a unified coordinate system for map production and quality inspection.

[0151] This embodiment also provides a machine-readable storage medium and a computer device. Figure 8 This is a schematic diagram of a machine-readable storage medium 801 according to an embodiment of the present invention. Figure 9 This is a schematic diagram of a computer device 903 according to an embodiment of the present invention.

[0152] The machine-readable storage medium 801 stores a machine-executable program 802 thereon, which, when executed by a processor, implements the method for multi-sensor calibration parameters of any of the above embodiments.

[0153] The computer device 903 may include a memory 901, a processor 902, and a machine-executable program 802 stored in the memory 901 and running on the processor 902, and the processor 902 executes the machine-executable program 802 to implement the method of multi-sensor calibration parameters of any of the above embodiments.

[0154] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, such as calculating lever values, may be specifically implemented in any machine-readable storage medium for use by, or in conjunction with, instruction execution systems, apparatuses, or devices (such as computer-based systems, processor-based systems, or other systems that can fetch and execute instructions from, an instruction execution system, apparatus, or device).

[0155] For the purposes of this embodiment, the machine-readable storage medium 801 can be any means capable of containing, storing, communicating, propagating, or transmitting a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the machine-readable storage medium 801 include: an electrical connection (electronic device) having one or more wires, a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, the machine-readable storage medium 801 can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0156] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system.

[0157] Computer device 903 can be, for example, a server, desktop computer, laptop computer, tablet computer, or smartphone. In some examples, computer device 903 can be a cloud computing node. Computer device 903 can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., that perform specific tasks or implement specific abstract data types. Computer device 903 can be implemented in a distributed cloud computing environment where tasks are performed by remote processing devices linked via a communication network. In a distributed cloud computing environment, program modules can reside on local or remote computing system storage media, including storage devices.

[0158] Computer device 903 may include a processor 902 adapted to execute stored instructions and a memory 901 that provides temporary storage space for the operation of said instructions during operation. The processor 902 may be a single-core processor, a multi-core processor, a computing cluster, or any other configuration. The memory 901 may include random access memory (RAM), read-only memory, flash memory, or any other suitable storage system.

[0159] The processor 902 can be connected via a system interconnect (e.g., PCI, PCI-Express, etc.) to an I / O interface (input / output interface) suitable for connecting the computer device 903 to one or more I / O devices (input / output devices). I / O devices may include, for example, a keyboard and indicating devices, where indicating devices may include a touchpad or touchscreen, etc. I / O devices may be built into the computer device 903 or may be external devices connected to the computing device.

[0160] The processor 902 may also be linked via a system interconnect to a display interface suitable for connecting the computer device 903 to a display device. The display device may include a display screen as a built-in component of the computer device 903. The display device may also include an external computer monitor, television, or projector connected to the computer device 903. Furthermore, a network interface controller (NIC) may be adapted to connect the computer device 903 to a network via a system interconnect. In some embodiments, the NIC may use any suitable interface or protocol (such as an Internet Minicomputer System Interface) to transmit data. The network may be a cellular network, a radio network, a wide area network (WAN), a local area network (LAN), or the Internet, etc. Remote devices may connect to the computing device via the network.

[0161] The flowchart provided in this embodiment is not intended to indicate that the operations of the method will be performed in any particular order, or that all operations of the method are included in every case. Furthermore, the method may include additional operations. Within the scope of the technical concept provided by the method in this embodiment, additional variations can be made to the above method.

[0162] Therefore, those skilled in the art should recognize that although numerous exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications conforming to the principles of the present invention can be directly determined or derived from the disclosure of the present invention without departing from the spirit and scope of the invention. Thus, the scope of the present invention should be understood and construed as covering all such other variations or modifications.

Claims

1. A method for calibrating parameters of multiple sensors, comprising: A first coordinate system is established with the total station as the origin, and the coordinate values ​​of multiple sensors are obtained. The multiple sensors include: lidar, inertial navigation, GNSS antenna and camera. The coordinate values ​​include the first coordinate value of lidar, the second coordinate value of inertial navigation, the third coordinate value of GNSS antenna and the fourth coordinate value of camera. The coordinate values ​​include the X value, Y value and Z value of the sensor in the first coordinate system. The first coordinate system is converted into a second coordinate system with the inertial navigation system as the origin. The second coordinate system records the target coordinate values ​​generated after the coordinate values ​​are converted in the second coordinate system. The target coordinate values ​​include the first target coordinate values ​​of the lidar, the second target coordinate values ​​of the inertial navigation system, the third target coordinate values ​​of the GNSS antenna, and the fourth target coordinate values ​​of the camera. The target coordinate values ​​include the X, Y, and Z values ​​of the multiple sensors in the second coordinate system. Calculate the lever arm value between one or more of the target coordinate values ​​(first target coordinate value, second target coordinate value, third target coordinate value, and fourth target coordinate value) and the inertial navigation coordinate value, wherein the inertial navigation coordinate value is the origin in the second coordinate system; The L2I calibration parameters are calculated based on the collected route information and the lever arm value. The L2I calibration parameters are used to calibrate the relative positional relationship between the lidar and the inertial navigation system. The camera's intrinsic parameters are calculated using data collected by the camera. The L2C calibration parameters are obtained by cloud computing based on the camera intrinsic parameters and the photos and laser points in the calibration board data. The L2C calibration parameters are used to calibrate the relative positional relationship between the main lidar and the camera. The C2I calibration parameters are calculated using a preset formula based on the L2I calibration parameters and the L2C calibration parameters. The C2I calibration parameters are used to calibrate the relative positional relationship between the camera and the inertial navigation system. The preset formula includes: C2I = L2I × L2C^(-1). Collect the main laser point cloud and the secondary laser point cloud generated by the main lidar and the secondary lidar facing the same scene at the same time; The main laser point cloud and the secondary laser point cloud are imported into the first preset calibration program for calculation to obtain the calibration parameters of the main and secondary lidars. The calibration parameters of the main and secondary lidars are used to calibrate the relative positional relationship between the main lidar and the secondary lidar. The L2I calibration parameters and the primary and secondary lidar calibration parameters are imported into the second preset calibration program for calculation to obtain the calibration parameters between the secondary lidar and the inertial navigation system. The calibration parameters between the secondary lidar and the inertial navigation system are used to calibrate the relative positional relationship between the secondary lidar and the inertial navigation system.

2. The method for calibrating parameters of multiple sensors according to claim 1, wherein, The first coordinate system and the second coordinate system also include: the front wheel point and the rear wheel point of the information collection vehicle; The step of converting the first coordinate system to a second coordinate system with the inertial navigation system as the origin includes: Import the first coordinate system into the preset program; Connect the front wheel point and the rear wheel point in the first coordinate system; Draw a perpendicular line along the rear wheel and measure the angle between the line and the perpendicular line; Rotate all measurement points in the first coordinate system around the rear wheel point along the connecting line until they coincide with the vertical line; The coordinate axes in the first coordinate system are redefined, and the second coordinate system is generated with the inertial navigation point as the origin. The vertical line is the positive direction of the Y-axis, and the right vertical line is the positive direction of the X-axis. The coordinates and Z values ​​of each point of the plurality of sensors in the second coordinate system are calculated to generate the first target coordinate value, the second target coordinate value, the third target coordinate value, and the fourth target coordinate value.

3. The method for calibrating parameters of multiple sensors according to claim 1, wherein, The step of calculating the lever arm value between one or more of the target coordinate values ​​(first, second, third, and fourth) and the inertial navigation coordinate values ​​includes: The first azimuth angle from the rear wheel to the front wheel in the first coordinate system and the second azimuth angle from the inertial navigation system to each measurement point in the first coordinate system are calculated using the azimuth angle calculation formula. The straight-line distance from the inertial navigation system to the measurement point is calculated using the following formula: where ΔX 2 惯导→测量点 represents the square of the X-axis distance from the inertial navigation to the measuring point, ΔY 2 惯导→测量点 represents the square of the Y-axis distance from the inertial navigation to the measuring point; The azimuth difference Δα1 is obtained by subtracting the first azimuth from the second azimuth. with the coordinates of the inertial navigation system as the origin, i.e. X 惯导 =0, Y 惯导 =0; the coordinate values of the measuring point are calculated by the following formula: X 测量点 = X 惯导 + S 惯导→测量点 * sin Δα1; Y 测量点 =Y 惯导 +S 惯导→测量点 *cos△α1; Z 测量点 =Z 测量点中心 -Z 惯导坐标轴中心 ; Among them, X 测量点、 Y 测量点 and Z 测量点 S represents the coordinate value of the measurement point in a coordinate system with the coordinates of the inertial navigation system as the origin. 惯导→测量点 This represents the straight-line distance from the inertial navigation system to the measurement point.

4. The method for calibrating parameters of multiple sensors according to claim 1, wherein, The step of calculating the camera's intrinsic parameters using data collected by the camera includes: Obtain the calibration board image generated by the camera; The calibration plate photos are imported into a preset tool to calculate the camera intrinsic parameters. The camera intrinsic parameters include: camera focal length, principal point coordinates, radial distortion, tangential distortion, and reprojection error.

5. The method for calibrating parameters of multiple sensors according to claim 1, wherein, The step of calculating the L2C calibration parameters based on the camera intrinsic parameters includes: The camera and the lidar collect a preset number of calibration board data at different positions, heights, and rotational angles. The calibration board data includes photographs and lidar point clouds. Obtain the camera's intrinsic parameters; Fill in the configuration file according to the camera intrinsic parameters; The L2C calibration parameters are obtained by importing the photograph, the laser point cloud, and the configuration file into a preset calibration program.

6. The method for calibrating parameters of multiple sensors according to claim 1, wherein, The step of calculating the C2I calibration parameters based on the L2I calibration parameters and the L2C calibration parameters includes: The L2I calibration parameters and the L2C calibration parameters are imported into a preset program software, and the C2I calibration parameters are generated by a preset formula.

7. A multi-sensor calibration system for implementing the method for multi-sensor calibration parameters according to any one of claims 1 to 6, comprising: The information collection vehicle is equipped with multiple sensors, including lidar, inertial navigation, GNSS antenna and camera. Each sensor can record and collect surrounding data in its own coordinate system. A calibration device for fusing the relative positional relationships of the sensors into a single inertial navigation coordinate system, comprising: The lever arm value measurement and calculation module is used to calculate the lever arm value from the GNSS antenna and the lidar to the center of the inertial navigation coordinate system. The L2I calibration module is used to calibrate the relative positional relationship between the lidar and the inertial navigation system; The camera intrinsic parameter calibration module is used to determine the specific parameter configuration of the camera's internal parameters; The L2C calibration module is used to calibrate the relative positional relationship between the main lidar and the camera; The C2I calibration module is used to calibrate the relative positional relationship between the camera and the inertial navigation system; A primary and secondary lidar calibration module is used to calibrate the relative positional relationship between the primary lidar and the secondary lidar; The secondary lidar and inertial navigation calibration module is used to calibrate the relative positional relationship between the secondary lidar and the inertial navigation system.

8. The multi-sensor calibration system according to claim 7, wherein, The lever arm value measurement and calculation module is also configured to: A first coordinate system is established with the total station as the origin, and the coordinate values ​​of multiple sensors are obtained. The multiple sensors include: lidar, inertial navigation, GNSS antenna and camera. The coordinate values ​​include the first coordinate value of lidar, the second coordinate value of inertial navigation, the third coordinate value of GNSS antenna and the fourth coordinate value of camera. The coordinate values ​​include the X value, Y value and Z value of the sensor in the first coordinate system. The first coordinate system is converted into a second coordinate system with the inertial navigation system as the origin. The second coordinate system records the target coordinate values ​​generated after the coordinate values ​​are converted in the second coordinate system. The target coordinate values ​​include the first target coordinate values ​​of the lidar, the second target coordinate values ​​of the inertial navigation system, the third target coordinate values ​​of the GNSS antenna, and the fourth target coordinate values ​​of the camera. The target coordinate values ​​include the X, Y, and Z values ​​of the multiple sensors in the second coordinate system. Calculate the lever arm value between one or more of the target coordinate values ​​(first target coordinate value, second target coordinate value, third target coordinate value, and fourth target coordinate value) and the inertial navigation coordinate value, wherein the inertial navigation coordinate value is the origin in the second coordinate system.

9. The multi-sensor calibration system according to claim 8, wherein, The L2I calibration module is further configured to: collect route information, convert the route information and the boom value of the GNSS antenna into a coordinate trajectory information file; and convert the coordinate trajectory information file and the boom value of the lidar into L2I calibration parameters. The camera intrinsic parameter calibration module is also configured to: acquire the calibration board image generated by the camera; The calibration plate image is imported into a preset tool to calculate the camera intrinsic parameters, which include: camera focal length, principal point coordinates, radial distortion, tangential distortion, and reprojection error. The L2C calibration module is further configured to: acquire the camera intrinsic parameters of the camera; fill in the configuration file according to the camera intrinsic parameters; import the photograph, the laser point cloud and the configuration file into a preset calibration program to calculate the L2C calibration parameters; The C2I calibration module is further configured to: acquire L2C calibration parameters; import the L2I calibration parameters and the L2C calibration parameters into a preset program software, and generate C2I calibration parameters using a preset formula; and The preset formula includes: C2I=L2I×L2C^(-1).

10. The multi-sensor calibration system according to claim 9, wherein, The main and secondary lidar calibration module is further configured to: collect the main lidar point cloud and the secondary lidar point cloud generated by the main lidar and the secondary lidar facing the same scene at the same time; import the main lidar point cloud and the secondary lidar point cloud into a preset calibration program for calculation to obtain the main and secondary lidar calibration parameters; The secondary lidar and inertial navigation calibration module is further configured to: import the L2I calibration parameters and the primary and secondary lidar calibration parameters into a preset calibration program for calculation to obtain the calibration parameters between the secondary lidar and the inertial navigation system.

11. A machine-readable storage medium having a machine-executable program stored thereon, the machine-executable program, when executed by a processor, implementing the method for multi-sensor calibration parameters according to any one of claims 1 to 6.

12. A computer device comprising a memory, a processor, and a machine-executable program stored in the memory and running on the processor, wherein the processor, when executing the machine-executable program, implements the method for multi-sensor calibration parameters according to any one of claims 1 to 6.

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