Calibration method and system of vehicle-mounted laser radar based on multiple mechanical arms

Abstract

The invention relates to a calibration method and system for a vehicle-mounted laser radar based on multiple mechanical arms, and the method comprises the steps: M1, carrying out the calibration of the vehicle-mounted laser radar disposed on the multiple mechanical arms, collecting data information of motion trails of multiple groups of mechanical arms, data information of motion trails of laser radars and data information of positions of the laser radars; and M2, based on the data information of the motion tracks of the multiple groups of mechanical arms and the data information of the motion track of the laser radar, fusing the motion track points of the laser radar and the multiple groups of mechanical arms by adopting a cyclic shift fusion algorithm of track points based on Rabras distribution, and the fused data information of the motion track points of the laser radar is obtained. The method not only can adapt to the requirements of different sensor types and complex environments and improve the flexibility and universality of the system, but also ensures that the relative position relationship between the sensors can be accurately controlled, thereby improving the calibration precision.

Description

Technical Field

[0001] The present invention relates to the technical field of laser radar calibration, and in particular to a calibration method and system for a vehicle-mounted laser radar based on multiple mechanical arms. Background Art

[0002] With the continuous development and popularization of autonomous driving technology, automotive-grade LiDAR has become one of the core components of autonomous vehicles. In actual production, each autonomous vehicle needs to be calibrated to ensure the accuracy and stability of the radar. However, the traditional calibration method requires each vehicle to be calibrated individually, which is time-consuming, labor-intensive and costly.

[0003] Existing radar calibration is based on the fact that the vehicle needs to be completely off the production line and the high voltage power is completed before the radar calibration work is allowed. This greatly increases the calibration time and it is impossible to directly put the calibrated radar into a fixed position for the same vehicle model.

[0004] In the field of sensor calibration, especially in the joint calibration of multiple sensors (such as radar and camera), the existing technology has the following main problems:

[0005] 1. Limited calibration accuracy: Since the relative position relationship between sensors is difficult to accurately control, the calibration accuracy is limited, which affects the subsequent fusion and utilization of sensor data.

[0006] 2. High system complexity: Existing calibration methods often require complex equipment and processes, such as the use of calibration boards and motion estimation algorithms, which increase the complexity and cost of the system.

[0007] 3. Lack of flexibility: Existing calibration methods are often targeted at specific sensor combinations and scenarios, lack sufficient flexibility, and are difficult to adapt to the needs of different sensor types and complex environments. Summary of the invention

[0008] In view of the above problems, the present invention provides a calibration method and system for a vehicle-mounted lidar based on a multi-robotic arm, which can not only adapt to the needs of different sensor types and complex environments, improve the flexibility and universality of the system, but also ensure that the relative position relationship between sensors can be precisely controlled, thereby improving the calibration accuracy.

[0009] In order to achieve the above-mentioned purpose and other related purposes, the technical solution provided by the present invention is as follows:

[0010] A calibration method for a vehicle-mounted laser radar based on a multi-mechanical arm, the method comprising:

[0011] M1. During the calibration process of the vehicle-mounted laser radar set on the multi-manipulator, data information of the motion trajectories of multiple sets of manipulators, data information of the motion trajectories of the laser radar, and data information of the position of the laser radar are collected;

[0012] M2. Based on the data information of the motion trajectories of the multiple sets of manipulators and the data information of the motion trajectories of the laser radar, a cyclic shift fusion algorithm of trajectory points based on Labras distribution is used to fuse the motion trajectory points of the laser radar and the multiple sets of manipulators to obtain the fused data information of the motion trajectory points of the laser radar;

[0013] M3. Based on the data information of the motion trajectory points of the fused laser radar and the data information of the position of the laser radar, a three-dimensional calibration space model of the laser radar is constructed, the calibration matrix of the laser radar is characterized, and the data information of the calibration matrix of the laser radar is obtained;

[0014] M4. Based on the data information of the calibration matrix of the laser radar, a calibration function F of the laser radar is established, and the calibration result of the laser radar is extrapolated to obtain the data information of the calibration result of the laser radar.

[0015] Furthermore, the method further comprises:

[0016] M5. Based on the data information of the laser radar calibration result, establish the laser radar verification function Q,

[0017]

[0018] Among them, x is the data information of the laser radar calibration result, α1, α2 and α3 are the bias factors of the laser radar, the laser radar calibration result is evaluated, and the data information of the laser radar calibration result evaluation value is output.

[0019] Furthermore, based on the data information of the evaluation value of the calibration result of the laser radar, a preset threshold is set. If the evaluation value of the calibration result of the laser radar is less than the preset threshold, the requirement is met and the calibration is completed. If the evaluation value of the calibration result of the laser radar is greater than the threshold, the requirement is not met and the process returns to step M2.

[0020] Further, in step M2, the cyclic shift fusion algorithm based on the trajectory points of the Labras distribution is used to fuse the motion trajectory points of the laser radar and the multiple groups of robotic arms, including:

[0021] M21. Based on the data information of the motion trajectories of the multiple sets of robotic arms, establish the Labras distribution function W of the multiple sets of robotic arms,

[0022]

[0023] Wherein, y is the data information of the motion trajectories of the multiple sets of robotic arms, β1, β2 and β3 are the scale parameters of the motion trajectories of the multiple sets of robotic arms, and the Labras distribution of the motion trajectories of the multiple sets of robotic arms is characterized to obtain the data information of the Labras distribution of the motion trajectories of the multiple sets of robotic arms;

[0024] M22. Based on the data information of the laser radar's motion trajectory, establish the Labras distribution function R of the laser radar,

[0025]

[0026] Wherein, z is the data information of the motion trajectory of the laser radar, δ1, δ2 and δ3 are the scale parameters of the motion trajectory of the laser radar, and the Labras distribution of the motion trajectory of the laser radar is characterized to obtain the data information of the Labras distribution of the motion trajectory of the laser radar;

[0027] M23. Based on the data information of the Labras distribution of the motion trajectory of the laser radar and the data information of the Labras distribution of the motion trajectory of the multiple sets of robotic arms, a cyclic shift fusion function U of the trajectory point is established,

[0028]

[0029] Among them, r1 is the data information of the Labrador distribution of the motion trajectory of the laser radar, r2 is the data information of the Labrador distribution of the motion trajectories of multiple groups of robotic arms, γ1, γ2 and γ3 are the fusion factors of the trajectory points. The motion trajectory points of the laser radar and multiple groups of robotic arms are fused to obtain the data information of the motion trajectory points of the fused laser radar.

[0030] Furthermore, the constraints of the fusion factors γ1, γ2 and γ3 of the trajectory points are:

[0031] Furthermore, the constraint function f1 of the scale parameters δ1, δ2 and δ3 of the motion trajectory of the laser radar is,

[0032]

[0033] The constraint function f2 of the scale parameters β1, β2 and β3 of the motion trajectories of the multiple sets of robotic arms is,

[0034]

[0035] Among them, the value range of constraint function f1 is (0,1), and the value range of constraint function f2 is (2,4).

[0036] Furthermore, in step M3, the three-dimensional calibration space model of the laser radar is constructed, and the calibration matrix of the laser radar is characterized, including:

[0037] M31. Based on the data information of the motion trajectory points of the fused laser radar and the data information of the position of the laser radar, construct a relative position sequence function P of the laser radar,

[0038] Among them, h1 is the data information of the motion trajectory point of the fused laser radar, h2 is the data information of the position of the laser radar, η1, η2 and η3 are the bias parameters of the laser radar, and the relative position sequence of the laser radar is calculated to obtain the data information of the relative position sequence of the laser radar;

[0039] M32. Input the data information of the relative position sequence of the laser radar into the three-dimensional calibration space model of the laser radar for training and learning, and determine the three-dimensional calibration space function S of the laser radar,

[0040]

[0041] Among them, q is the data information of the relative position sequence of the laser radar, λ1, λ2 and λ3 are the three-dimensional calibration factors of the laser radar, and the data information of the relative position sequence of the trained laser radar is obtained;

[0042] M33. Based on the data information of the relative position sequence of the trained laser radar, the data information of the motion trajectory points of the fused laser radar and the data information of the position of the laser radar are input to characterize the calibration matrix of the laser radar and obtain the data information of the calibration matrix of the laser radar.

[0043] Furthermore, the three-dimensional calibration factors λ1, λ2 and λ3 of the laser radar are:

[0044]

[0045] Among them, q is the data information of the relative position sequence of the laser radar.

[0046] Furthermore, the calibration function F of the laser radar is:

[0047]

[0048] Among them, g is the data information of the laser radar calibration matrix, and μ1, μ2 and μ3 are the penalty coefficients of the laser radar calibration results.

[0049] In order to achieve the above-mentioned purpose and other related purposes, the present invention also provides a computer-readable storage medium, which stores a computer program programmed or configured to execute any one of the calibration methods for the multi-robotic arm-based vehicle-mounted laser radar.

[0050] The present invention has the following positive effects:

[0051] 1. The present invention fuses the motion trajectory points of the laser radar and multiple groups of robotic arms by adopting a cyclic shift fusion algorithm of trajectory points based on Labrador distribution, and characterizes the calibration matrix of the laser radar by combining the construction of a three-dimensional calibration space model of the laser radar. This not only ensures that the relative position relationship between sensors can be accurately controlled, thereby improving the calibration accuracy, but also simplifies the calibration equipment and process, reduces the dependence on the calibration board, and reduces the system complexity and cost.

[0052] 2. The present invention establishes a calibration function F of the laser radar, calculates the calibration result of the laser radar, and obtains data information of the calibration result of the laser radar. It can not only adapt to the needs of different sensor types and complex environments, and improve the flexibility and universality of the system, but also accurate calibration helps to reduce the deviation and error between sensor data, thereby improving the accuracy and reliability of data fusion. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a schematic diagram of the method flow of the present invention;

[0054] Figure 2 A schematic diagram of the flow of a cyclic shift fusion algorithm of trajectory points based on Labrador distribution of the present invention;

[0055] Figure 3 A schematic diagram of the process of constructing a three-dimensional calibration space model of a laser radar according to the present invention; DETAILED DESCRIPTION

[0056] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0057] Example 1: Figure 1 As shown, a calibration method for a vehicle-mounted laser radar based on a multi-mechanical arm, the method comprising:

[0058] M1. During the calibration process of the vehicle-mounted laser radar set on the multi-manipulator, data information of the motion trajectories of multiple sets of manipulators, data information of the motion trajectories of the laser radar, and data information of the position of the laser radar are collected;

[0059] M2. Based on the data information of the motion trajectories of the multiple sets of manipulators and the data information of the motion trajectories of the laser radar, a cyclic shift fusion algorithm of trajectory points based on Labras distribution is used to fuse the motion trajectory points of the laser radar and the multiple sets of manipulators to obtain the fused data information of the motion trajectory points of the laser radar;

[0060] M3. Based on the data information of the motion trajectory points of the fused laser radar and the data information of the position of the laser radar, a three-dimensional calibration space model of the laser radar is constructed, the calibration matrix of the laser radar is characterized, and the data information of the calibration matrix of the laser radar is obtained;

[0061] M4. Based on the data information of the calibration matrix of the laser radar, a calibration function F of the laser radar is established, and the calibration result of the laser radar is extrapolated to obtain the data information of the calibration result of the laser radar.

[0062] In this embodiment, the method further includes:

[0063] M5. Based on the data information of the laser radar calibration result, establish the laser radar verification function Q,

[0064]

[0065] Among them, x is the data information of the laser radar calibration result, α1, α2 and α3 are the bias factors of the laser radar, the laser radar calibration result is evaluated, and the data information of the laser radar calibration result evaluation value is output.

[0066] In this embodiment, a preset threshold is set based on the data information of the calibration result evaluation value of the laser radar. If the calibration result evaluation value of the laser radar is less than the preset threshold, the requirement is met and the calibration is completed. If the calibration result evaluation value of the laser radar is greater than the threshold, the requirement is not met and the process returns to step M2.

[0067] In this embodiment, if Figure 2 As shown, in step M2, the cyclic shift fusion algorithm based on the trajectory points of the Labras distribution is used to fuse the motion trajectory points of the laser radar and multiple groups of mechanical arms, including:

[0068] M21. Based on the data information of the motion trajectories of the multiple sets of robotic arms, establish the Labras distribution function W of the multiple sets of robotic arms,

[0069]

[0070] Wherein, y is the data information of the motion trajectories of the multiple sets of robotic arms, β1, β2 and β3 are the scale parameters of the motion trajectories of the multiple sets of robotic arms, and the Labras distribution of the motion trajectories of the multiple sets of robotic arms is characterized to obtain the data information of the Labras distribution of the motion trajectories of the multiple sets of robotic arms;

[0071] M22. Based on the data information of the laser radar's motion trajectory, establish the Labras distribution function R of the laser radar,

[0072]

[0073] Wherein, z is the data information of the motion trajectory of the laser radar, δ1, δ2 and δ3 are the scale parameters of the motion trajectory of the laser radar, and the Labras distribution of the motion trajectory of the laser radar is characterized to obtain the data information of the Labras distribution of the motion trajectory of the laser radar;

[0074] M23. Based on the data information of the Labras distribution of the motion trajectory of the laser radar and the data information of the Labras distribution of the motion trajectory of the multiple sets of robotic arms, a cyclic shift fusion function U of the trajectory point is established,

[0075]

[0076] Among them, r1 is the data information of the Labrador distribution of the motion trajectory of the laser radar, r2 is the data information of the Labrador distribution of the motion trajectories of multiple groups of robotic arms, γ1, γ2 and γ3 are the fusion factors of the trajectory points. The motion trajectory points of the laser radar and multiple groups of robotic arms are fused to obtain the data information of the motion trajectory points of the fused laser radar.

[0077] In this embodiment, the constraints of the fusion factors γ1, γ2 and γ3 of the trajectory points are:

[0078]

[0079] In this embodiment, the constraint function f1 of the scale parameters δ1, δ2 and δ3 of the motion trajectory of the laser radar is,

[0080]

[0081] The constraint function f2 of the scale parameters β1, β2 and β3 of the motion trajectories of the multiple sets of robotic arms is,

[0082]

[0083] Among them, the value range of constraint function f1 is (0,1), and the value range of constraint function f2 is (2,4).

[0084] Example 2: Based on the vehicle-mounted laser radar calibration method based on multiple mechanical arms in Example 1, the present invention is further illustrated and described below.

[0085] like Figure 1 As shown, a calibration method for a vehicle-mounted laser radar based on a multi-mechanical arm, the method comprising:

[0086] M1. During the calibration process of the vehicle-mounted laser radar set on the multi-manipulator, data information of the motion trajectories of multiple sets of manipulators, data information of the motion trajectories of the laser radar, and data information of the position of the laser radar are collected;

[0087] M2. Based on the data information of the motion trajectories of the multiple sets of manipulators and the data information of the motion trajectories of the laser radar, a cyclic shift fusion algorithm of trajectory points based on Labras distribution is used to fuse the motion trajectory points of the laser radar and the multiple sets of manipulators to obtain the fused data information of the motion trajectory points of the laser radar;

[0088] M3. Based on the data information of the motion trajectory points of the fused laser radar and the data information of the position of the laser radar, a three-dimensional calibration space model of the laser radar is constructed, the calibration matrix of the laser radar is characterized, and the data information of the calibration matrix of the laser radar is obtained;

[0089] M4. Based on the data information of the calibration matrix of the laser radar, a calibration function F of the laser radar is established, and the calibration result of the laser radar is extrapolated to obtain the data information of the calibration result of the laser radar.

[0090] In this embodiment, if Figure 3 As shown, in step M3, the three-dimensional calibration space model of the laser radar is constructed, and the calibration matrix of the laser radar is characterized, including:

[0091] M31. Based on the data information of the motion trajectory points of the fused laser radar and the data information of the position of the laser radar, construct a relative position sequence function P of the laser radar,

[0092] Among them, h1 is the data information of the motion trajectory point of the fused laser radar, h2 is the data information of the position of the laser radar, η1, η2 and η3 are the bias parameters of the laser radar, and the relative position sequence of the laser radar is calculated to obtain the data information of the relative position sequence of the laser radar;

[0093] M32. Input the data information of the relative position sequence of the laser radar into the three-dimensional calibration space model of the laser radar for training and learning, and determine the three-dimensional calibration space function S of the laser radar,

[0094]

[0095] Among them, q is the data information of the relative position sequence of the laser radar, λ1, λ2 and λ3 are the three-dimensional calibration factors of the laser radar, and the data information of the relative position sequence of the trained laser radar is obtained;

[0096] M33. Based on the data information of the relative position sequence of the trained laser radar, the data information of the motion trajectory points of the fused laser radar and the data information of the position of the laser radar are input to characterize the calibration matrix of the laser radar and obtain the data information of the calibration matrix of the laser radar.

[0097] In this embodiment, the three-dimensional calibration factors λ1, λ2 and λ3 of the laser radar are:

[0098] Among them, q is the data information of the relative position sequence of the laser radar.

[0099] In this embodiment, the calibration function F of the laser radar is:

[0100]

[0101] Among them, g is the data information of the laser radar calibration matrix, μ1, μ2 and μ3 are the penalty coefficients of the laser radar calibration results.

[0102] In this embodiment, the present invention provides a computer-readable storage medium, on which is stored a computer program programmed or configured to execute any one of the calibration methods for a vehicle-mounted laser radar based on a multi-robotic arm.

[0103] In this embodiment, the present invention provides a computer-readable storage medium, on which is stored a computer program programmed or configured to execute any one of the calibration methods for a vehicle-mounted laser radar based on a multi-robotic arm.

[0104] Any reference to memory, storage, database or other media used in the embodiments provided in the present application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM) and memory bus dynamic RAM (RDRAM).

[0105] In summary, the present invention can not only adapt to the needs of different sensor types and complex environments and improve the flexibility and universality of the system, but also ensure that the relative position relationship between sensors can be accurately controlled, thereby improving the calibration accuracy.

[0106] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A calibration method for a vehicle-mounted laser radar based on a multi-manipulator, characterized in that: The method comprises: M1. During the calibration process of the vehicle-mounted laser radar set on the multi-manipulator, data information of the motion trajectories of multiple sets of manipulators, data information of the motion trajectories of the laser radar, and data information of the position of the laser radar are collected; M2. Based on the data information of the motion trajectories of the multiple sets of manipulators and the data information of the motion trajectories of the laser radar, a cyclic shift fusion algorithm of trajectory points based on Labras distribution is used to fuse the motion trajectory points of the laser radar and the multiple sets of manipulators to obtain the fused data information of the motion trajectory points of the laser radar; M3. Based on the data information of the motion trajectory points of the fused laser radar and the data information of the position of the laser radar, a three-dimensional calibration space model of the laser radar is constructed, the calibration matrix of the laser radar is characterized, and the data information of the calibration matrix of the laser radar is obtained; M4. Based on the data information of the calibration matrix of the laser radar, a calibration function F of the laser radar is established, and the calibration result of the laser radar is extrapolated to obtain the data information of the calibration result of the laser radar.

2. The calibration method of the vehicle-mounted laser radar based on multiple mechanical arms according to claim 1 is characterized in that: The method further comprises: M5. Based on the data information of the laser radar calibration result, establish the laser radar verification function Q, Among them, x is the data information of the laser radar calibration result, α1, α2 and α3 are the bias factors of the laser radar, the laser radar calibration result is evaluated, and the data information of the laser radar calibration result evaluation value is output.

3. The calibration method of the vehicle-mounted laser radar based on multiple mechanical arms according to claim 2 is characterized in that: Based on the data information of the calibration result evaluation value of the laser radar, a preset threshold is set. If the calibration result evaluation value of the laser radar is less than the preset threshold, the requirements are met and the calibration is completed. If the calibration result evaluation value of the laser radar is greater than the threshold, the requirements are not met and return to step M2.

4. The calibration method of the vehicle-mounted laser radar based on multiple mechanical arms according to claim 1 is characterized in that: In step M2, the cyclic shift fusion algorithm based on the trajectory points of the Labras distribution is used to fuse the motion trajectory points of the laser radar and the multiple groups of robotic arms, including: M21. Based on the data information of the motion trajectories of the multiple sets of robotic arms, establish the Labras distribution function W of the multiple sets of robotic arms, Wherein, y is the data information of the motion trajectories of the multiple sets of robotic arms, β1, β2 and β3 are the scale parameters of the motion trajectories of the multiple sets of robotic arms, and the Labras distribution of the motion trajectories of the multiple sets of robotic arms is characterized to obtain the data information of the Labras distribution of the motion trajectories of the multiple sets of robotic arms; M22. Based on the data information of the laser radar's motion trajectory, establish the Labras distribution function R of the laser radar, Wherein, z is the data information of the motion trajectory of the laser radar, δ1, δ2 and δ3 are the scale parameters of the motion trajectory of the laser radar, and the Labras distribution of the motion trajectory of the laser radar is characterized to obtain the data information of the Labras distribution of the motion trajectory of the laser radar; M23. Based on the data information of the Labras distribution of the motion trajectory of the laser radar and the data information of the Labras distribution of the motion trajectory of the multiple sets of robotic arms, a cyclic shift fusion function U of the trajectory point is established, Among them, r1 is the data information of the Labrador distribution of the motion trajectory of the laser radar, r2 is the data information of the Labrador distribution of the motion trajectories of multiple groups of robotic arms, γ1, γ2 and γ3 are the fusion factors of the trajectory points. The motion trajectory points of the laser radar and multiple groups of robotic arms are fused to obtain the data information of the motion trajectory points of the fused laser radar.

5. The calibration method of the vehicle-mounted laser radar based on multiple mechanical arms according to claim 4 is characterized in that: The constraints of the fusion factors γ1, γ2 and γ3 of the trajectory points are:

6. The calibration method of the vehicle-mounted laser radar based on multiple mechanical arms according to claim 4 is characterized in that: The constraint function f1 of the scale parameters δ1, δ2 and δ3 of the laser radar's motion trajectory is, The constraint function f2 of the scale parameters β1, β2 and β3 of the motion trajectories of the multiple sets of robotic arms is, Among them, the value range of constraint function f1 is (0,1), and the value range of constraint function f2 is (2,4).

7. The calibration method of the vehicle-mounted laser radar based on multiple mechanical arms according to claim 1 is characterized in that: In step M3, the three-dimensional calibration space model of the laser radar is constructed, and the calibration matrix of the laser radar is characterized, including: M31. Based on the data information of the motion trajectory points of the fused laser radar and the data information of the position of the laser radar, construct a relative position sequence function P of the laser radar, Among them, h1 is the data information of the motion trajectory point of the fused laser radar, h2 is the data information of the position of the laser radar, η1, η2 and η3 are the bias parameters of the laser radar, and the relative position sequence of the laser radar is calculated to obtain the data information of the relative position sequence of the laser radar; M32. Input the data information of the relative position sequence of the laser radar into the three-dimensional calibration space model of the laser radar for training and learning, and determine the three-dimensional calibration space function S of the laser radar, Among them, q is the data information of the relative position sequence of the laser radar, λ1, λ2 and λ3 are the three-dimensional calibration factors of the laser radar, and the data information of the relative position sequence of the trained laser radar is obtained; M33. Based on the data information of the relative position sequence of the trained laser radar, the data information of the motion trajectory points of the fused laser radar and the data information of the position of the laser radar are input to characterize the calibration matrix of the laser radar and obtain the data information of the calibration matrix of the laser radar.

8. The calibration method of the vehicle-mounted laser radar based on multiple mechanical arms according to claim 7 is characterized in that: The three-dimensional calibration factors λ1, λ2 and λ3 of the laser radar are, Among them, q is the data information of the relative position sequence of the laser radar.

9. The calibration method of the vehicle-mounted laser radar based on multiple mechanical arms according to claim 1, characterized in that: The calibration function F of the laser radar is, Among them, g is the data information of the laser radar calibration matrix, μ1, μ2 and μ3 are the penalty coefficients of the laser radar calibration results.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program that is programmed or configured to execute the calibration method for a vehicle-mounted laser radar based on a multi-mechanical arm as described in any one of claims 1 to 9.

Images