WO2021237520A1

WO2021237520A1 - Method and apparatus for calibrating extrinsics, and device and storage medium

Info

Publication number: WO2021237520A1
Application number: PCT/CN2020/092652
Authority: WO
Inventors: 湛逸飞
Original assignee: 华为技术有限公司
Priority date: 2020-05-27
Filing date: 2020-05-27
Publication date: 2021-12-02
Also published as: CN112654886A; CN112654886B

Abstract

Disclosed are a method and apparatus for calibrating extrinsics, and a device and a storage medium, which belong to the field of autonomous driving. The method comprises: measuring a first device by using a measuring device; determining a coordinate system conversion relationship between the measuring device and the first device; measuring at least one calibration plane by respectively using the measuring device and a second device; determining at least one plane group, to which the at least one calibration plane is mapped respectively under a coordinate system of the measuring device and a coordinate system of the second device; and determining a coordinate system conversion relationship between the measuring device and the second device by using the at least one plane group. Extrinsics is obtained by means of a determined plane group without the need to extract homonymy points from point cloud data, such that the influence of an extraction process of homonymy points on calibration precision is avoided, thereby improving the calibration precision.

Description

External parameter calibration method, device, equipment and storage medium

Technical field

This application relates to the field of automatic driving, and in particular to an external parameter calibration method, device, equipment and storage medium.

Background technique

In the fields of surveying and mapping, automatic driving, etc., it is often necessary to convert the data measured by the device from the coordinate system of the device itself to other coordinate systems. In order to realize the conversion of the coordinate system, it is necessary to determine the correspondence between the coordinate systems of different devices, that is, calibration. External parameters between different devices.

Taking lidar as the device to be calibrated as an example, the related technology will first scan the entire room in a three-dimensional space (such as a room) with a measuring device in the process of Lidar calibration, and obtain the calibration object in the three-dimensional space according to the scanning result. The point coordinates of the mapped point under the coordinate system of the, then, scan the entire room through the lidar in the three-dimensional space to obtain the point cloud data, and extract the point coordinates of the point mapped by the calibration object from the point cloud data; after obtaining two After the point coordinates, the correspondence relationship between the coordinate system of the lidar and the coordinate system of the three-dimensional space is determined according to the matching relationship between the points with the same name (that is, the points mapped by the calibration object in the two coordinate systems).

The above method needs to extract the point coordinates of the point mapped by the calibration object from the point cloud data when determining the external parameters. However, due to the ranging error of the lidar itself and the insufficient resolution, it is difficult to accurately extract the point mapped by the calibration object Therefore, the calibration accuracy of this method is poor.

Summary of the invention

The embodiments of the present application provide an external parameter calibration method, device, equipment, and storage medium, which can improve the accuracy of external parameter calibration. The technical solution is as follows:

In a first aspect, an external parameter calibration method is provided. In this method, a first calibration parameter is obtained according to the measurement data of a first device by a measuring device, and the first calibration parameter is used to indicate the relationship between the measuring device and the The coordinate system conversion relationship between the first devices; determine at least one first plane mapped by the at least one calibration plane in the coordinate system of the measurement device according to the measurement data of the measurement device on the at least one calibration plane; According to the measurement data of the at least one calibration plane by the second device, determine at least one second plane mapped by the at least one calibration plane in the coordinate system of the second device; according to the at least one first plane and the The at least one second plane determines at least one plane group, the plane group includes a first plane and a second plane, and the first plane in the plane group corresponds to the second plane; according to the at least one plane group, it is determined A second calibration parameter, where the second calibration parameter is used to indicate the coordinate system conversion relationship between the measuring device and the second device; according to the first calibration parameter and the second calibration parameter, the External parameters between the second device and the first device.

The external parameter calibration timing is obtained by the above method. Because the external parameters are obtained through the determined plane group, there is no need to extract the points with the same name from the point cloud data, thus avoiding the influence of the extraction process of the points with the same name on the calibration accuracy, thus improving The calibration accuracy is improved. In addition, the method can be solidified into a computer automated execution process, avoiding the time-consuming and laborious problems caused by manual calculation of calibration parameters, thereby improving the calibration efficiency.

Optionally, the determining the second calibration parameter according to the at least one plane group includes: according to the at least one plane group, the first plane and the second plane in the plane group satisfy a matching condition, and determining the second Calibration parameters.

Optionally, the first plane and the second plane in the plane group satisfy a matching condition, including: the normal vector angle between the first plane and the second plane in the plane group is the smallest.

Optionally, the second calibration parameter includes a rotation matrix, and according to the at least one plane group, the normal vector angle between the first plane and the second plane in the plane group is the smallest, and the second calibration is determined The parameters include: determining the rotation matrix according to the at least one plane group and a first optimization function, where the rotation matrix makes the value of the first optimization function a minimum value.

Through the above optional method, because the first optimization function is constructed, multiple calibration data and the first optimization function are used, and the optimization method is used to automatically obtain the rotation matrix. On the one hand, the solution process of the rotation matrix can be calibrated by external parameters. The equipment is automated without manual intervention, thereby improving calibration efficiency and avoiding errors caused by manual intervention. On the other hand, the rotation matrix can be automatically obtained through multiple calibration data, reducing the error caused by a single calibration.

Optionally, the first plane and the second plane in the plane group satisfy a matching condition, including: the distance between the first plane and the second plane in the plane group is the smallest.

By adopting the above-mentioned optional method, because the plane matching relationship is used to solve the external parameters between the devices, the step of selecting points with the same name is omitted, and higher calibration accuracy is obtained.

Optionally, the second calibration parameter includes a translation matrix, and according to the at least one plane group, the distance between the first plane and the second plane in the plane group is the smallest, and the second calibration parameter is determined, including : Determine the translation matrix according to the at least one plane group and the second optimization function, and the translation matrix makes the value of the second optimization function a minimum value.

Through the above optional method, due to the construction of the second optimization function, using multiple calibration data and the second optimization function, the optimization method is used to automatically obtain the translation matrix. On the one hand, the calculation process of the translation matrix can be calibrated by external parameters. It is completed automatically without manual intervention, thereby improving calibration efficiency and avoiding errors caused by manual intervention. On the other hand, the translation matrix can be automatically obtained through multiple calibration data, reducing the error caused by a single calibration.

Optionally, the second calibration parameter includes a translation matrix, and the determining the second calibration parameter according to the at least one plane group includes: using the rotation matrix and the initial translation matrix to perform a calculation on a point on the first plane Rotation transformation and translation transformation are used to obtain the projection point of the point; according to the at least one plane group, an initial translation matrix that minimizes the distance between the projection point and the second plane is determined as the translation matrix.

Through the above optional methods, considering that even if the normal vector angle between the first plane and the second plane is the smallest, it may happen that the first plane and the second plane are not completely parallel, but between the first plane and the second plane. The situation of intersection makes it difficult to directly calculate the distance between the first plane and the second plane, which in turn makes it difficult to determine the translation matrix based on the distance between the planes. Through the above method, the distance calculation between the two surfaces is converted into the distance calculation between the point and the plane. Since the first plane and the second plane are parallel or non-parallel, the difference between the projection point and the second plane is The distances are easy to solve, which ensures that the method of determining the translation matrix has a wider application range and improves the practicability.

Optionally, the acquiring the first calibration parameter according to the measurement data of the measuring device on the first device includes: according to the coordinate value of the mark point on the first device in the coordinate system of the first device and the coordinate value of the first device. The coordinate value of the marker point measured by the measuring device in the coordinate system of the measuring device is used to obtain the first calibration parameter.

In the case that the first device does not support the observation function, there may be a technical problem that it is difficult to obtain the coordinate system of the first device. With the above optional method, the coordinate system of the first device can be calculated by observing the mark points on the first device with the measuring device, which provides a way to obtain the coordinate system of the first device through passive observation, which helps Improve the accuracy of the obtained coordinate system of the first device (that is, the first calibration parameter).

Optionally, the measurement device is a total station, a laser scanner or a photogrammetry system, the calibration plane is a calibration board or a wall, the first device is an inertial navigation device, a vehicle or a first lidar, and the The second device is a second lidar, millimeter wave or camera.

In a second aspect, an external parameter calibration device is provided, and the external parameter calibration device includes:

An acquiring module, configured to acquire a first calibration parameter according to the measurement data of the first device by the measuring device, where the first calibration parameter is used to indicate the coordinate system conversion relationship between the measuring device and the first device;

A determining module, configured to determine at least one first plane mapped by the at least one calibration plane in the coordinate system of the measuring device according to the measurement data of the at least one calibration plane by the measuring device;

A determining module, configured to determine at least one second plane mapped by the at least one calibration plane in the coordinate system of the second device according to the measurement data of the at least one calibration plane by the second device;

A determining module, configured to determine at least one plane group according to the at least one first plane and the at least one second plane, the plane group including a first plane and a second plane, the first plane in the plane group Corresponding to the second plane;

A determining module, configured to determine a second calibration parameter according to the at least one plane group, where the second calibration parameter is used to indicate a coordinate system conversion relationship between the measuring device and the second device;

The acquiring module is further configured to acquire external parameters between the second device and the first device according to the first calibration parameter and the second calibration parameter.

Wherein, the external parameter calibration device is a device with computing capability, for example, the external parameter calibration device is a computing device, a processor, a chip, a personal computer, etc.

Optionally, the determining module is configured to determine the second calibration parameter according to the at least one plane group, and the first plane and the second plane in the plane group satisfy a matching condition.

Optionally, the second calibration parameter includes a rotation matrix, and the determination module is configured to determine the rotation matrix according to the at least one plane group and a first optimization function, and the rotation matrix enables the first optimization The value of the function is the minimum value.

Optionally, the second calibration parameter includes a translation matrix, and the determining module is configured to determine the translation matrix according to the at least one plane group and a second optimization function, and the translation matrix enables the second optimization The value of the function is the minimum value.

Optionally, the second calibration parameter includes a translation matrix, and the determining module is configured to use the rotation matrix and the initial translation matrix to perform rotation transformation and translation transformation on a point on the first plane to obtain Projection point; according to the at least one plane group, determine an initial translation matrix that minimizes the distance between the projection point and the second plane as the translation matrix.

Optionally, the acquisition module is configured to use the coordinate value of the marker point on the first device in the coordinate system of the first device and the marker point measured by the measuring device in the measurement The coordinate value in the coordinate system of the device is used to obtain the first calibration parameter.

In a third aspect, an external parameter calibration device is provided. The external parameter calibration device includes a processor for executing instructions so that the external parameter calibration device executes the first aspect or any one of the optional methods of the first aspect. The external parameter calibration method provided. For the specific details of the external reference calibration device provided by the third aspect, reference may be made to the foregoing first aspect or any of the optional methods of the first aspect, and will not be repeated here.

In a fourth aspect, a computer-readable storage medium is provided. The storage medium stores at least one instruction. The instruction is read by a processor to enable an external reference calibration device to execute the first aspect or any one of the first aspects. Select the external parameter calibration method provided by the method.

In a fifth aspect, a computer program product is provided. When the computer program product runs on an external parameter calibration device, the external parameter calibration device executes the external parameter provided in the first aspect or any one of the optional methods in the first aspect. Calibration method.

In a sixth aspect, a chip is provided, when the chip runs on an external parameter calibration device, the external parameter calibration device executes the external parameter calibration method provided in the first aspect or any one of the optional methods of the first aspect.

In a seventh aspect, an external parameter calibration system is provided. The external parameter calibration system includes an external parameter calibration device, a measuring device, a first device, and a second device. The external parameter calibration device is used to perform the first aspect or the first aspect described above. The method described in any of the optional manners in the aspect.

Description of the drawings

FIG. 1 is a schematic diagram of an application scenario of external parameter calibration of lidar provided by an embodiment of the present application;

2 is a schematic diagram of the architecture of a high-precision map collection system provided by an embodiment of the present application;

3 is a schematic diagram of a calibration device for external parameters in a high-precision map acquisition system provided by an embodiment of the present application;

4 is a schematic diagram of the device name, specification parameters and reference diagram of an external parameter calibration device provided by an embodiment of the present application;

FIG. 5 is a flowchart of an external parameter calibration method 300 provided by an embodiment of the present application;

Fig. 6 is a schematic diagram of a coordinate system of a GNSS/IMU device provided by an embodiment of the present application;

FIG. 7 is a flowchart of an external parameter calibration method 400 provided by an embodiment of the present application;

FIG. 8 is a schematic structural diagram of an external parameter calibration device 500 provided by an embodiment of the present application;

FIG. 9 is a schematic structural diagram of an external parameter calibration device 600 provided by an embodiment of the present application.

Detailed ways

In order to make the purpose, technical solutions, and advantages of the present application clearer, the implementation manners of the present application will be further described in detail below in conjunction with the accompanying drawings.

In order to facilitate understanding, some terms related concepts involved in the embodiments of the present application are first introduced below.

Calibration is a process of obtaining equipment parameters. The purpose of calibration is to determine the values of some equipment parameters. Calibration includes internal parameter calibration and external parameter calibration.

External parameter calibration refers to the process of determining the coordinate system conversion relationship between equipment A and equipment B. Through the external parameters between device A and device B, the point in the coordinate system of device A can be mapped to the coordinate system of device B after rotation and translation, or vice versa, the point in the coordinate system of device B can be passed through After rotation and translation, it is mapped to the coordinate system of device A. For example, calibrating the external parameters between LiDAR (Light Detection and Ranging, LiDAR) and Global Navigation Satellite System (GNSS)/Inertial Measurement Unit (IMU) equipment is to obtain the coordinates of LiDAR The pose transformation relationship between the coordinate system to the GNSS/IMU device. The external parameters between two devices are usually expressed by a rotation matrix and a translation matrix.

Optionally, the external parameters between the two devices can be used

Express. Among them, R _LI is an example of a rotation matrix, and T _LI is an example of a translation matrix.

The rotation matrix represents the rotation transformation relationship of the coordinate system between the device A and the device B. Optionally, the rotation matrix is a matrix with three rows and three columns. The rotation matrix includes 3 degrees of freedom, which correspond to the x-axis, y-axis, and z-axis, respectively. The rotation transformation relationship of the three axes of the z axis. Optionally, the rotation matrix is represented _{by the following matrix R LI.}

Or, in order to simplify the expression, the rotation matrix is represented by a quaternion, and the quaternion is denoted as q _LI for example. The quaternion q _{LI is,} for example, (w, x, y, z). R _LI and q _LI are equivalent, and both represent rotation transformation.

The translation matrix represents the translation transformation relationship of the coordinate system between the device A and the device B. Optionally, the rotation matrix is a 3*1 size matrix, the rotation matrix includes 3 degrees of freedom, which correspond to the x-axis, y-axis, and z-axis, respectively, and the translation matrix represents the three x, y, and z The translation in the axis direction. For example, the translation matrix is represented _{by the following matrix T LI.}

T _LI =[t _x t _y t _z ] ^T

The external parameter calibration method provided by the embodiment of the present application can be applied to the external parameter calibration scenario of lidar. The following is a brief introduction to the external parameter calibration scene of the lidar.

Lidar is a new type of sensor. Lidar includes a laser transmitter and receiver. The laser transmitter generates and emits a light pulse, the light pulse hits the object and reflects back, and finally the light pulse is received by the receiver. The receiver accurately measures the propagation time of the light pulse from emission to reflection. According to the height of the laser transmitter and the laser scanning angle, the coordinates of each spot relative to the center of the lidar are accurately calculated.

Since the distance measurement accuracy of lidar can reach several centimeters, and the distance measurement accuracy is relatively accurate, lidar is widely used in surveying and mapping, intelligent driving and other fields. In the application process, it is often necessary to convert the point cloud information obtained by the lidar from the lidar coordinate system to other coordinate systems. For example, in the production of high-precision maps, it is necessary to use the laser point cloud in the laser radar scanning collection area, and the position and attitude information obtained by the positioning and attitude system (such as GNSS/IMU equipment). Refer to Figure 1, the external parameter calibration of lidar and GNSS/IMU equipment is required, that is, the conversion relationship between lidar coordinate system and GNSS/IMU equipment coordinate system is obtained, so as to use the external parameters between lidar and GNSS/IMU equipment. Participate, combine the multi-frame laser point cloud with the pose information of each frame moment to form a world point cloud.

The above describes the external parameter calibration scenario of lidar. The following is an example of the specific application of the external parameter calibration scenario of lidar, and introduces the technical effect of the method provided in this application in the application scenario.

In a possible implementation, the installation data of multiple sensors is obtained, and the relative position relationship between the sensors is calculated according to the installation data of each sensor, so as to calculate the external parameters between the sensors. The form of sensor installation data is not limited to all measurable mathematical models such as design drawings, computer aided design (CAD) drawings, and three-dimensional models. For example, according to the formula in the design drawing of the lidar, the center position of the lidar coordinate system is calculated. In the same way, calculate the center position of other sensors except lidar, and then calculate the relative positional relationship between lidar and other sensors in space.

However, when the above method is adopted, due to the actual installation error, the actual installation cannot be performed accurately according to the requirements of the design drawings, so installation errors will be introduced. Therefore, the accuracy of the external parameters calculated by only relying on the design drawing data is not high enough.

In a possible implementation, in a three-dimensional scene, such as a room, the three-dimensional coordinates of landmarks (such as wall corners, pillars, and other landmarks) in the entire room are obtained by scanning with high-precision three-dimensional measuring equipment. Then use the lidar to scan the entire room, extract the coordinates of each marker in the lidar point cloud, and determine the relationship between the lidar coordinate system and the three-dimensional space coordinate system through the matching relationship of the markers with the same name.

However, when the above-mentioned method is adopted, firstly, it is difficult to realize the establishment of a coordinate system conversion relationship between a sensor that does not support the observation function (such as a GNSS/IMU device) and the three-dimensional scene in question. That is, it is impossible to calibrate external parameters between GNSS/IMU equipment and lidar and camera. Second, to use matching points for calibration, it is necessary to extract the points corresponding to the three-dimensional model from the laser point cloud. In fact, the accuracy of the laser radar is generally ±2 centimeters (cm), so the accuracy of using this method is poor. Third, the equipment required to build a 3D scene model is very expensive, and the price of equipment with higher accuracy is in the million level, so the cost of using this method is too high.

In a possible implementation, according to the recorded height of the multi-line lidar and the attitude angle information of the multi-line lidar read by the GNSS/IMU device, determine the reference point of the multi-line lidar relative to the reference plane, and display it visually For the above reference point, adjust the calibration parameters between the GNSS/IMU device and the multi-line lidar according to the deviation between the displayed reference point and the corresponding actual point cloud. When the deviation displayed according to the adjusted calibration parameter is When it is zero, it is determined that the calibration is over.

However, when the above method is adopted, professionals are required to manually adjust the calibration parameters according to the principle of the scheme and the visualization results. Therefore, the disadvantage of this method is that it is time-consuming and labor-intensive and requires professional operations, and cannot be solidified into a process; secondly, it relies on manual labor and cannot be automated, and its accuracy relies on human observation results.

In a possible implementation, a multi-line lidar is used to scan a flat panel; according to the scanning results, the edge points of the flat panel are extracted and the flat panel edge lines are fitted; the corner points of the flat panel are obtained through the intersection of the two edge lines as the laser A known point in the radar coordinate system.

However, when the above method is adopted, the fitting edge line is a number of points (the number does not exceed the number of line bundles) obtained by scanning the edge of the flat panel with lidar, and its accuracy is difficult to guarantee. Moreover, it is impossible to obtain the accurate coordinates of the corner points in the GNSS/IMU device coordinate system. For example, in the case of using a total station, the corner points cannot be accurately sighted.

In the scenario of external parameter calibration between lidar and GNSS/IMU equipment, since the GNSS/IMU equipment itself cannot actively observe, its coordinate system cannot be obtained indirectly, and other reference objects must be used to obtain the coordinate system of the GNSS/IMU equipment. Secondly, the lidar itself has a ranging error, and its resolution is not high enough, it may not be able to accurately obtain the position of a point in space. In summary, it is difficult to calibrate external parameters of lidar and GNSS/IMU equipment and the accuracy is not high enough to meet the needs of high-precision map mapping.

In some embodiments of the present application, a high-precision and highly automated method for calibrating external parameters of lidar is proposed for the scene of external parameter calibration between the lidar and GNSS/IMU equipment in the high-precision map acquisition system. Observe the coordinate system of the GNSS/IMU device by using high-precision three-dimensional measurement equipment (such as a total station) combined with the mechanical size parameters of the GNSS/IMU device, and use the total station and lidar to simultaneously observe the calibration plane (such as the calibration flat panel) , Use the fitting relationship of the plane with the same name to construct the matching condition, and solve the rotation matrix and translation matrix step by step. Since points with the same name are avoided from the laser point cloud, the calibration accuracy is improved.

The following describes the system architecture provided by the embodiments of the present application.

Referring to FIG. 2, an embodiment of the present application provides a system architecture 100. The system architecture 100 is an example of a high-precision map collection system. Among them, the "high precision" in the high-precision map includes two meanings. On the one hand, it means that the accuracy of the coordinates in the map is higher, for example, the accuracy of the coordinates is at the centimeter level. On the other hand, it means that the road traffic information elements contained in the map are richer and more detailed. For example, the map includes not only roads, but also road shapes, traffic lights and other information.

The system architecture 100 includes a lidar 101, a GNSS/IMU device 102, a long focus camera 103, a short focus camera 104, an antenna 107, and a vehicle 105.

The GNSS/IMU device 102 is rigidly connected and fixed with the lidar 101, the telephoto camera 103, and the short-focus camera 104. The lidar 101, the GNSS/IMU device 102, the antenna 107, the telephoto camera 103, and the short telephoto camera 104 are arranged on a base 106, and the base 106 is arranged on the roof of the vehicle 105.

In the process of making a high-precision map, the lidar 101 is used to scan the laser point cloud in the collection area. The GNSS/IMU device 102 is used to obtain pose information.

Referring to FIG. 3, an embodiment of the present application provides a system architecture 200. The system architecture 200 is an example of a high-precision map collection system. For example, the system architecture 200 is suitable for application in the external parameter calibration scenario between the lidar 101 and the GNSS/IMU device 102 in the system architecture 100. The system architecture 200 includes a lidar 101, a GNSS/IMU device 102, a total station 201, multiple calibration boards, and a personal computer (PC). Optionally, the PC is another device with processing capabilities, such as a processor , Chips, etc. The PC is not shown in Figure 3. Referring to FIG. 4, FIG. 4 is an example of the device name, specification parameters, and reference diagram of each device involved in the system architecture 200.

Optionally, the total station 201 is a laser total station. The ranging accuracy of the total station 201 is, for example, 0.1 millimeter (mm). The total station 201 is set in a position that is in line with the GNSS/IMU device 102 and the calibration board.

The multiple calibration boards include a calibration board 2021, a calibration board 2022, and a calibration board 2023. The calibration board 2021, the calibration board 2022 and the calibration board 2023 are arranged in different positions. The calibration board 2021, the calibration board 2022, and the calibration board 2023 have different postures. Optionally, the calibration plate is an enamel calibration plate. Optionally, the calibration plate has a calibration aluminum oxide coating. Optionally, the specification of the calibration board is 1.0m*1.0m, that is, the width and height are each 1m. Among them, the material of the aluminum oxide coating is a highly reflective material, and the diffuse reflection of the aluminum oxide coating is relatively small. The surface of the enamel glass is very flat and not easily deformed.

The GNSS/IMU device 102 is an inertial navigation device to be calibrated. Optionally, the appearance of the GNSS/IMU device 102 is a box.

Optionally, the lidar 101 is a multi-beam lidar 101. The lidar 101 is set at a position where the calibration board can be observed. The lidar 101 and the GNSS/IMU device 102 are rigidly connected and fixed.

A solution program is installed and running in the PC, and the solution program is used to solve the rotation matrix and the translation matrix, so as to determine the external parameters between the lidar 101 and the GNSS/IMU device 102. The PC is connected to at least one of the lidar 101, the GNSS/IMU device 102, and the total station 201 through a wireless network or a wired network.

The system architecture is introduced above, and the method 300 to the method 400 are used to exemplarily introduce the method flow of external parameter calibration based on the system architecture provided above.

Referring to FIG. 5, FIG. 5 is a flowchart of an external parameter calibration method 300 provided by an embodiment of the present application.

The hardware devices involved in the method 300 include a measurement device, a first device, a second device, a calibration plane, and an external parameter calibration device.

Optionally, the measuring device is a high-precision three-dimensional measuring device. For example, the measurement equipment is a total station, a laser scanner, or a photogrammetric system.

Optionally, the calibration plane is any hardware device with a flat surface. Optionally, the calibration plane is a plane that the laser cannot penetrate. For example, the calibration plane is a calibration board or wall. Among them, by using the calibration board, it is helpful to obtain higher calibration accuracy.

The method 300 is used for external parameter calibration between the first device and the second device. Optionally, the first device and the second device are any two different devices. Optionally, the first device and the second device are any two different sensors. Optionally, the first device and the second device are respectively a sensor and a non-sensor, for example, the first device and the second device are a sensor and a vehicle body respectively. Optionally, the first device and the second device have the same device type. For example, both the first device and the second device are lidars, the first device is the first lidar, and the second device is the second lidar. Optionally, the first device and the second device have different device types. For example, the first device is an inertial navigation device or vehicle 105, and the second device is a lidar, millimeter wave, or camera. For example, the first device is a lidar, and the second device is a millimeter wave or a camera. Optionally, the first device is a device that does not support the observation function. For example, the first device is an inertial navigation device, for example, the first device is a GNSS/IMU device.

Optionally, the method 300 is executed interactively by the lidar 101, the total station 201, and the PC in the system architecture 200. For example, S301 of method 300 is pre-executed by total station 201, and the data measured by total station 201 on GNSS/IMU equipment 102 and the data measured by total station 201 on the calibration board are obtained. S305 of method 300 is determined by lidar 101. Execute in advance to obtain the data measured by the lidar 101 on the calibration plate. The data obtained by the total station 201 and the lidar 101 respectively are used as the input of the PC, and the PC executes S307 to S312. By implementing the method 300, the system architecture 200 can automatically obtain accurate external parameters between the lidar 101 and the GNSS/IMU device 102, that is, obtain the conversion relationship between the coordinate system of the lidar 101 and the coordinate system of the GNSS/IMU device 102. Using the external parameters between the lidar 101 and the GNSS/IMU device 102, multiple frames of laser point clouds can be combined with the pose information of each frame time to form a world point cloud.

Exemplarily, the method 300 includes S301 to S312.

S301. The measuring device measures the first device to obtain measurement data for the first device.

In some embodiments, there are multiple landmark points on the first device, and the measurement data is the coordinate value of each landmark point in the coordinate system of the measuring device among the multiple landmark points on the first device.

The mark point is located at a position with known coordinate values on the first device. In other words, the coordinate value of the marker point in the coordinate system of the first device can be determined in advance. Therefore, by using the coordinate values of the same marker point in the coordinate system of the first device and the coordinate values of the coordinate system of the measuring device, the coordinate system conversion relationship between the measuring device and the first device can be determined. Optionally, the number of marking points on the first device is at least 4. Optionally, multiple marking points on the first device are evenly distributed on the surface of the first device. Optionally, in the case that the first device itself does not have a mark point, manually mark the first device, and use the marked point as the mark point.

For example, the first device is a GNSS/IMU device, the measuring device is a total station, and the calibration plane is a calibration board. Set up a total station in advance at a position visible to the GNSS/IMU equipment and the calibration board to complete the station construction. During the execution of S301, the total station observes multiple landmark points with known coordinates on the GNSS/IMU equipment, conducts a rear intersection, and obtains the measurement data of the GNSS/IMU equipment. Wherein, the number of the multiple mark points is more than four.

S302. The measuring device transmits the measurement data of the first device to the external parameter calibration device.

How to transmit the measurement data to the external reference calibration equipment includes many ways. Optionally, the measurement data obtained by the measurement device is stored in a storage device, and the external parameter calibration device reads the measurement data from the storage device, thereby transmitting the measurement data to the external parameter calibration device through the storage device. The storage device includes but is not limited to U disk or mobile hard disk. Optionally, the measurement device directly transmits the measurement data of the first device to the external parameter calibration device. For example, the measurement device establishes a wireless network connection with the external parameter calibration device, and the measurement device transmits the measurement data to the external device through wireless communication. Participate in the calibration equipment. In another example, the measuring device is connected to the external parameter calibration device through a cable, and the measuring device transmits the measurement data to the external parameter calibration device through the cable.

S303. The measuring device measures at least one calibration plane to obtain measurement data.

The measuring device measures each calibration plane in at least one calibration plane to obtain measurement data corresponding to each calibration plane. Optionally, each calibration plane has at least one mark point, and the measuring device measures each mark point in each calibration plane separately to obtain measurement data. Optionally, there are at least nine marking points on a calibration plane. Optionally, all the marking points on a calibration plane are evenly distributed on the calibration plane, so as to prevent errors caused by the deformation of the calibration plane. For example, the measuring equipment is a total station, and the calibration plane is a calibration board. Use the total station to observe several marking points on the calibration board to obtain measurement data.

S304. The measuring device sends the measurement data of at least one calibration plane to the external parameter calibration device.

S305. The second device measures at least one calibration plane to obtain measurement data.

The second device measures each calibration plane in at least one calibration plane to obtain measurement data corresponding to each calibration plane. Optionally, each calibration plane has at least one mark point, and the second device measures each mark point in each calibration plane separately to obtain measurement data. For example, the second device is a lidar, and the calibration plane is a calibration board. The lidar is used to observe the calibration board and save point cloud data. The point cloud data is an example of the measurement data obtained by the second device.

In some embodiments, S303 and S305 are performed through multiple measurement processes. For example, the calibration plane is the calibration board. When the i-th measurement is performed, the calibration board is first set at position i, so that the calibration board has an attitude i. Then, the measuring equipment measures the calibration board of the position i and the posture i to obtain the measurement data of the i-th measurement. The second device measures the calibration board of position i and posture i, and obtains the measurement data of the i-th measurement. After that, when the (i+1)th measurement is performed, the position of the calibration plate is adjusted from position i to position i+1, and the posture of the calibration plate is adjusted from posture i to posture i+1. Then, the measuring device measures the calibration board at the position i+1 and the posture i+1 to obtain the measurement data of the (i+1)th measurement. The second device measures the calibration board at the position i+1 and the posture i+1, and obtains the measurement data of the (i+1)th measurement. By analogy, the data of n plane groups are obtained by performing n measurements on the calibration board. Among them, i is a positive integer, i is greater than or equal to 1 and less than or equal to n. n is a positive integer, and n is greater than or equal to 2. Optionally, n is greater than or equal to 20. In this way, due to repeated observations on the calibration plane, measurement errors can be reduced.

S306. The second device sends the measurement data of the at least one calibration plane to the external parameter calibration device.

S307. The external parameter calibration device acquires the first calibration parameter according to the measurement data of the first device by the measuring device.

The first calibration parameter is used to indicate the coordinate system conversion relationship between the measuring device and the first device. The first calibration parameter is also called the coordinate system of the first device observed by the measuring device. Specifically, the first calibration parameter includes at least one of a rotation matrix or a translation matrix. The rotation matrix represents the rotation transformation relationship from the coordinate system of the measuring device to the coordinate system of the first device. The translation matrix represents the translation transformation relationship from the coordinate system of the measuring device to the coordinate system of the first device. For example, for the point A in the coordinate system of the measuring device, the rotation matrix in the first calibration parameter is used to rotate the point A, and the translation matrix in the first calibration parameter is used to translate the point A. Get the point with the same name of point A in the coordinate system of the first device.

How to determine the first calibration parameter includes multiple implementation methods. In a possible implementation, the external parameter calibration device obtains the coordinate value of the mark point on the first device in the coordinate system of the first device, and according to the coordinate value of the mark point on the first device in the coordinate system of the first device And the coordinate value of the marker point measured by the measuring device in the coordinate system of the measuring device to obtain the first calibration parameter.

For example, the first device is a GNSS/IMU device, the measuring device is a total station, and the external reference calibration device obtains the coordinate value of the marker point on the GNSS/IMU device in the coordinate system of the GNSS/IMU device, and calculates the total station The coordinate value of the marker point measured in the coordinate system relative to the coordinate system of the GNSS/IMU device, thereby obtaining the conversion relationship between the coordinate system of the total station and the coordinate system of the GNSS/IMU device. Among them, please refer to Figure 6, which is an example of the coordinate system of the GNSS/IMU device. The conversion relationship between the coordinate system of the total station and the coordinate system of the GNSS/IMU device is an example of the first calibration parameter. For example, a first calibration parameters and represented by the following equation T _TI R _TI (1) is, R _TI and T _TI also referred to a coordinate system of the total station observations GNSS / IMU device.

The meaning of Equation (1) is any point in C _T p _T after R _TI for rotational transform, T _TI and after translation transform, the same name can be obtained p _T p _I site in the C _I. In equation (1), p _T represents any point in the coordinate system of the total station. R _TI represents the rotation matrix from the total station to the GNSS/IMU device. T _TI represents the translation matrix from the total station to the GNSS/IMU device. p _I represents a point in the GNSS/IMU device coordinate system. C _T represents the coordinate system of the total station, and C _I represents the coordinate system of the GNSS/IMU device.

For the sake of brevity, in each equation involved in this embodiment, the superscript "T" is used to indicate that the data has been transposed, for example

Represents the transposition of _{p T,}

Represents the transposition of _{p L.}

For the sake of brevity, in each equation involved in this embodiment, the subscript "capital English letter" is used to indicate the device corresponding to the data. Specifically, the subscript "T" is used to indicate the data corresponding to the total station, the subscript "I" is used to indicate the data corresponding to the GNSS/IMU device, and the subscript "L" is used to indicate the data corresponding to the lidar. For example, p _T represents a point in the total station coordinate system, and p _L represents a point in the lidar coordinate system. In addition, the subscript "W" represents the world.

For the sake of brevity, in each equation involved in this embodiment, the subscript "2 uppercase English letters" is used to indicate that the data is data corresponding to two devices. Specifically, the subscript "TI" indicates the data between the total station and the GNSS/IMU device, and the subscript "LT" indicates the data between the total station and the lidar. For example, as in the above equation (1), R _TI represents the rotation matrix from the total station to the GNSS/IMU device.

This paragraph introduces the technical effects of the above methods. In the case that the first device does not support the observation function, there may be a technical problem that it is difficult to obtain the coordinate system of the first device. In the above method, the coordinate system of the first device is calculated by observing the mark points on the first device with the measuring device, which provides a way to obtain the coordinate system of the first device through passive observation, which helps to improve the acquisition. The accuracy of the coordinate system of the first device (that is, the first calibration parameter). For example, the measuring device is a total station, and the first device is a GNSS/IMU device. By using a total station to observe the marking points on the outer surface of the GNSS/IMU device, and combining the size parameters of the GNSS/IMU equipment (ie the coordinate value of the marking point on the GNSS/IMU device in the GNSS/IMU device coordinate system), the GNSS is calculated The coordinate system of /IMU equipment solves the problem that the coordinate system of GNSS/IMU equipment is difficult to obtain. In addition, due to the high observation accuracy of the total station, the accuracy of the acquired coordinate system of the GNSS/IMU device is also high.

S308. The external parameter calibration device determines at least one first plane mapped by the at least one calibration plane in the coordinate system of the measuring device according to the measurement data of the at least one calibration plane by the measuring device.

The first plane is the plane mapped by the indicator plane in the coordinate system of the measuring device. Optionally, the first plane is represented by parameters in the plane equation. Optionally, the at least one first plane determined by the external parameter calibration device and the at least one calibration plane have a one-to-one correspondence. For example, the i-th first plane determined by the external parameter calibration device is a plane mapped by the i-th calibration plane in the coordinate system of the measuring device. Optionally, the first plane is determined by plane fitting. The plane fitting method is, for example, a principal component analysis (PCA) method.

Among them, the PCA method includes, for example, centering the three-dimensional coordinates of the point cloud of the calibration plane, obtaining the covariance matrix and diagonalizing, and obtaining three eigenvalues. The eigenvector corresponding to the smallest eigenvalue is the normal vector of the calibration plane. . Bring in the coordinates of a point arbitrarily and normalize it to get the plane equation of the first plane.

For example, the calibration plane is a calibration board, the measuring equipment is a total station, and the external parameter calibration equipment is a PC. After using the total station to measure the calibration plate for the i-th time, the PC will calculate the space plane equation of the calibration plate in the total station coordinate system by plane fitting, as shown in the following equation (2).

a _i X+b _i Y+c _i Z+1=0; equation (2)

In equation _{_{(2), (a i, b i,}} c i) represents the plane of the calibration plate at a mapping coordinate system of the total station i measurement. The value of i is greater than or equal to 1 and less than or equal to n. n is the number of measurements. By analogy, after using the total station to measure the calibration board n times, (a ₁ , b ₁ , c ₁ ), (a ₂ , b ₂ , c ₂ )...(a _i , b _i , c _i ) And (a _n , b _n , c _n ) these n sets of data, these n sets of data represent n first planes.

S309. The external parameter calibration device determines at least one second plane mapped by the at least one calibration plane in the coordinate system of the second device according to the measurement data of the at least one calibration plane by the second device.

The second plane is a plane where the indicator plane is mapped in the coordinate system of the second device. Optionally, the second plane is represented by parameters in the plane equation. Optionally, the at least one second plane determined by the external parameter calibration device and the at least one calibration plane have a one-to-one correspondence. For example, the i-th second plane determined by the external parameter calibration device is a plane mapped by the i-th calibration plane in the coordinate system of the second device. Optionally, the second plane is determined by plane fitting. The plane fitting method is, for example, the PCA method. For the PCA method, please refer to the introduction of S308 above.

For example, the calibration plane is a calibration board, the second device is a lidar, and the external parameter calibration device is a PC. The point cloud data is obtained after the i-th measurement of the calibration board is carried out using lidar. The PC segmentation extracts the point cloud of the calibration plate in the point cloud data, and calculates the spatial plane equation of the calibration plate in the lidar coordinate system by plane fitting, as shown in the following equation (3).

A _i X+B _i Y+C _i Z+1=0; equation (3)

In equation (3), (A _i , B _i , C _i ) represents the plane mapped by the calibration plate in the lidar coordinate system during the i-th measurement. The value of i is greater than or equal to 1 and less than or equal to n. n is the number of measurements. By analogy, after using the lidar to measure the calibration board n times, you will get (A ₁ , B ₁ , C ₁ ), (A ₂ , B ₂ , C ₂ ), ... (A _i, B _i , C _i ),...(A _n , B _n , C _n ) These n sets of data, these n sets of data represent n second planes.

S310. The external parameter calibration device determines at least one plane group according to the at least one first plane and the at least one second plane.

A plane group includes a first plane and a second plane. The first plane in the plane group corresponds to the second plane. For example, the first plane and the second plane in the plane group are two planes respectively mapped on the same calibration plane. For example, the plane group i includes a first plane i and a second plane i. Wherein, the first plane i is a plane mapped by the calibration plane i in the coordinate system of the measuring device. The second plane i is a plane mapped by the calibration plane i in the coordinate system of the second device. Alternatively, the plane is determined by the group i group i of the plane data obtained to achieve the data plane includes a group i _{_{(a i, b i, c}} i) and _{_{p i, (A i, B}} i, C i) P _i, and , The normal vector of the plane and the center point of the plane. _{_{Wherein, (a i, b i,}} c i) represents the i-th first plane measured. _Pi represents a point on the plane under the coordinate system of the first device (such as a GNSS/IMU device). (A _i, B _i , C _i ) represents the second plane obtained by the i-th measurement. P _i represents a point on the plane under the coordinate system of the second device (such as lidar) corresponding to _{p i.} Wherein, the plane group i is an example of one plane group in at least one plane group.

In some embodiments, the number of plane groups determined by the external parameter calibration device is multiple. Optionally, the number of plane groups determined by the external parameter calibration device is equal to the number of times of measuring the calibration plane. For example, after the measurement device and the second device are used to measure the calibration plane n times, the external parameter calibration device will determine n plane groups.

S311. The external parameter calibration device determines a second calibration parameter according to at least one plane group.

Wherein, the second calibration parameter is used to indicate the coordinate system conversion relationship between the measuring device and the second device. Specifically, the second calibration parameter includes at least one of a rotation matrix or a translation matrix. The rotation matrix represents the rotation transformation relationship from the coordinate system of the measuring device to the coordinate system of the second device. The translation matrix represents the translation transformation relationship from the coordinate system of the measuring device to the coordinate system of the second device. For point A in the coordinate system of the measuring equipment, the rotation matrix in the second calibration parameter is used to rotate the point A, and the translation matrix in the second calibration parameter is used to translate the point A to obtain the point A point with the same name in the coordinate system of the second device.

For example, the measuring device is a total station, the second device is a lidar, and the second calibration parameter is used to indicate the coordinate system conversion relationship between the total station and the lidar. The second calibration parameter can be determined by the following equation (4) Parameter representation.

The meaning of Equation (4) is, C _L through any point p _L R _LT and after the rotational transformation T _LT posterior translation transform, to obtain a point p _T p _L of the same name in the C _T. In equation (4), p _L represents any point in the coordinate system of the lidar. R _LT represents the rotation matrix between the total station and the lidar, and T _LT represents the rotation matrix between the total station and the lidar. p _T represents the point in the coordinate system of the total station. _CL represents the coordinate system of the lidar. C _T represents the coordinate system of the total station.

In some embodiments, the external parameter calibration device uses the plane matching relationship to solve the second calibration parameter. Among them, the plane matching relationship refers to the matching relationship between the two planes respectively mapped on the same calibration plane in the coordinate system of the measuring device and the second device, that is, between the first plane and the second plane group in the same plane group. The matching relationship between. Specifically, the external parameter calibration device determines the second calibration parameter according to at least one plane group, the first plane and the second plane in the plane group satisfy the matching condition. Wherein, the first plane and the second plane in the plane group satisfy the matching condition, including the following condition A and condition B.

Condition A, the angle between the normal vector of the first plane and the second plane in the plane group is the smallest. For example, the first plane and the second plane are parallel or approximately parallel.

Condition B, the distance between the first plane and the second plane in the plane group is the smallest. For example, the distance between the first plane and the second plane is zero or close to zero. In other words, the first plane and the second plane are coincident or approximately coincident.

In some embodiments, when the external parameter calibration device respectively fits the first plane mapped by the calibration plane and the second plane mapped by the calibration plane by plane fitting, the solution is solved so that the first plane and the second plane have the same name. The calibration parameters of the plane are used as the second calibration parameters. Among them, the plane with the same name refers to the same plane in two coordinate systems. The fact that the first plane and the second plane are planes with the same name is an example of the first plane and the second plane satisfying the matching condition.

This paragraph introduces the effect of using the plane matching relationship to solve the second calibration parameter. In the method of matching the points with the same name to solve the calibration parameters, the accuracy of the selected points with the same name is not high, and there will be technical problems that affect the accuracy of the calibration. For example, in the case that the second device is a lidar, if the calibration parameters are solved by selecting the points with the same name in the lidar and using the point-to-matching method, the calibration accuracy will not be high enough due to the certain ranging error of the lidar. Using the above method, by performing plane fitting and using the plane matching relationship to solve the conversion relationship between the lidar coordinate system and the GNSS/IMU device coordinate system, the step of selecting the same-named point in the lidar is eliminated, so as to obtain higher The calibration accuracy.

In some embodiments, the second calibration parameter is solved by an optimization method. For example, the rotation matrix and the translation matrix in the second calibration parameter are respectively determined by two optimization functions. The optimization function is also called the cost function or the objective function. In order to distinguish the description, in this embodiment, the optimization function used to determine the rotation matrix is referred to as the first optimization function, and the optimization function used to determine the translation matrix is referred to as the second optimization function.

In some embodiments, the external parameter calibration device determines a rotation matrix in the second calibration parameter based on at least one plane group and the first optimization function, and the rotation matrix makes the value of the first optimization function the smallest value.

The first optimization function is used to determine the normal vector angle between the first plane and the second plane according to the initial rotation matrix and at least one plane group. The input parameters of the first optimization function include an initial rotation matrix and at least one plane group, and the value of the first optimization function is used to indicate the size of the normal vector angle between the first plane and the second plane in the plane group.

For example, the expression of the first optimization function is as follows.

f ₁ =min(1-R _LT *(A,B,C)*(a,b,c))||min(1-R _LT *((A,B,C)))

Among them, f ₁ represents the first optimization function. The meaning of f ₁ is that the normal vector angle between the two matching planes is the smallest. The symbol "||" means or. (1-R _LT *(A,B,C)*(a,b,c)) and (1+R _LT *((A,B,C))) both represent the first plane and the first plane in the plane group The normal vector angle between the two planes specifically refers to the normal vector angle between the second plane represented by (A, B, C) and the first plane represented by (a, b, c).

How to use the first optimization function to determine the rotation matrix includes many ways. In a possible implementation, the rotation matrix in the second calibration parameter is adjusted on the basis of the initial rotation matrix in the first optimization function. For example, determine the initial rotation matrix in the first optimization function; bring the initial rotation matrix and the data of at least one plane group into the first optimization function respectively, and determine the value of the first optimization function. In this process, the initial rotation matrix in the first optimization function is adjusted. When the value of the first optimization function reaches the minimum value, the initial rotation matrix in the first optimization function is determined as the rotation matrix in the second calibration parameter.

In this embodiment, by constructing the first optimization function, using multiple calibration data and the first optimization function, the optimization method is used to automatically obtain the rotation matrix. On the one hand, the calculation process of the rotation matrix can be automatically completed by the external parameter calibration equipment , Without manual intervention, thereby improving calibration efficiency and avoiding errors caused by manual intervention. On the other hand, the rotation matrix can be automatically obtained through multiple calibration data, reducing the error caused by a single calibration.

In some embodiments, the external parameter calibration device determines a translation matrix according to the at least one plane group and the second optimization function, and the translation matrix makes the value of the second optimization function a minimum value.

The second optimization function is used to determine the distance between the first plane and the second plane according to the initial translation matrix and the at least one plane group. The input parameters of the second optimization function include an initial translation matrix and at least one plane group, and the value of the second optimization function is used to indicate the size of the distance between the first plane and the second plane in the plane group.

For example, the expression of the second optimization function is as follows.

f ₂ =min((R _LT *P+T _LT -p)*(a, b, c))

Among them, f ₂ represents the second optimization function. The meaning of f ₂ is the smallest distance between two matching planes. R _LT represents the rotation matrix determined by the first optimization function. T _LT represents the initial translation matrix. (R _LT *P+T _LT -p)*(a, b, c) represents the distance between the first plane and the second plane in the plane group, specifically referring to the first plane represented by (A, B, C) The distance between the second plane and the first plane indicated by (a, b, c). When _{the value of f 2} is close to 0, the first plane and the second plane coincide. P represents a point on the first plane. p represents a point on the second plane.

How to use the second optimization function to determine the translation matrix includes many ways. In a possible implementation, the translation matrix in the second calibration parameter is adjusted on the basis of the initial translation matrix in the second optimization function. For example, determine the initial translation matrix in the second optimization function; bring the initial translation matrix and the data of at least one plane group into the second optimization function respectively, and determine the value of the second optimization function. In this process, the initial translation matrix in the second optimization function is adjusted. When the value of the second optimization function reaches the minimum value, the initial translation matrix in the second optimization function is determined as the translation matrix in the second calibration parameter.

In this embodiment, by constructing the second optimization function, using multiple calibration data and the second optimization function, the optimization method is used to automatically obtain the translation matrix. On the one hand, the calculation process of the translation matrix can be automatically completed by the external parameter calibration equipment , Without manual intervention, thereby improving calibration efficiency and avoiding errors caused by manual intervention. On the other hand, the translation matrix can be automatically obtained through multiple calibration data, reducing the error caused by a single calibration.

In some embodiments, the rotation matrix and the translation matrix are obtained step by step. Specifically, the rotation matrix is first determined according to at least one plane group; then, the translation matrix is determined according to the determined rotation matrix and the at least one plane group.

How to use the determined rotation matrix to determine the translation matrix includes many ways. In a possible implementation, the external parameter calibration device uses the determined rotation matrix and the initial translation matrix to perform rotation transformation and translation transformation on the point on the first plane to obtain the projection point of the point; the external parameter calibration device is based on at least A plane group determines the initial translation matrix that minimizes the distance between the projection point and the second plane as the translation matrix.

Optionally, using the determined rotation matrix to determine the translation matrix is achieved by the optimization function described above. For example, the value of the second optimization function is the distance between the projection point of the point on the first plane and the second plane. The input parameters of the second optimization function include the rotation matrix. After the rotation matrix is determined by the first optimization function, the rotation matrix and the initial translation matrix determined by the first optimization function are brought into the second optimization function. In the process of calculating through the second optimization function, a point P is taken on the first plane; the rotation matrix determined by the first optimization function is used to rotate the point P, and the initial translation matrix is used to translate the point P, Obtain the projection point P'of the point P. Calculate the distance between the projection point P'and the second plane. When the value of the distance between the projection point P'and the second plane reaches the minimum value, the initial rotation matrix in the second optimization function is determined as the rotation matrix in the second calibration parameter.

By using the determined rotation matrix to determine the translation matrix, the effects achieved include: considering that even if the normal vector angle between the first plane and the second plane is the smallest, it may appear that the first plane and the second plane are not completely parallel, and It is a situation where the first plane and the second plane intersect, which makes it difficult to directly calculate the distance between the first plane and the second plane, which in turn makes it difficult to determine the translation matrix based on the distance between the planes. Through the above method, the distance calculation between the two surfaces is converted into the distance calculation between the point and the plane. Since the first plane and the second plane are parallel or non-parallel, the difference between the projection point and the second plane is The distances are easy to solve, which ensures that the method of determining the translation matrix has a wider application range and improves the practicability.

Among them, how to determine the initial rotation matrix and the initial translation matrix include many ways. In a possible implementation, for a plane group, the first point on the first plane and the second point on the second plane are obtained, and the initial rotation matrix is determined by matrix decomposition according to the first point and the second point And the initial translation matrix. Optionally, the first point is any point on the first plane, and the second point is any point on the second plane. In this embodiment, the first point and the second point are not required to be points with the same name. Optionally, the first point is the center point of the first plane. The second point is the center point of the second plane.

For example, the first device is a GNSS/IMU device, and the second device is a lidar. For plane group i, take a point p on the plane in the coordinate system of the GNSS/IMU device and a point P in the plane of the corresponding laser point cloud. Through the following equation (5), the initial R _LT and the initial T _{LT are} obtained by matrix decomposition. Among them, the initial R _LT is an example of the initial rotation matrix, and the initial T _LT is an example of the initial translation matrix.

p*R _LT + T _LT ＝P; equation (5)

S312. The external parameter calibration device acquires the external parameter between the second device and the first device according to the first calibration parameter and the second calibration parameter.

In this embodiment, since the first device and the calibration plane are measured by the measuring device, and the calibration plane is measured by the second device, the coordinate system of the measuring device can serve as a gap between the coordinate system of the first device and the coordinate system of the second device. The relay. According to the first calibration parameter obtained in step S307 and the second calibration parameter obtained in step S311, the external parameter between the second device and the first device can be determined. Wherein, the external parameters between the second device and the first device include a rotation matrix between the second device and the first device and a translation matrix between the second device and the first device. In a possible implementation, equation (1) and equation (4) are combined to obtain the following equation (6).

The meaning of equation (6) is that any point p _T _{in C T} undergoes rotation transformation through R _LT and R _TI respectively, and after _{translation transformation through T LT} and T _TI _{respectively, the point p I} of the same name in _{C I} can be obtained. In equation (6), p _L represents a point in the coordinate system of the lidar. R _LT represents the rotation matrix between the total station and the lidar. T _LT represents the rotation matrix between the total station and the lidar. R _TI represents the rotation matrix from the total station to the GNSS/IMU device. T _TI represents the translation matrix from the total station to the GNSS/IMU device. p _I represents a point in the coordinate system of the GNSS/IMU device. C _T represents the coordinate system of the total station, and C _I represents the coordinate system of the GNSS/IMU device. _CL represents the coordinate system of the lidar.

In some embodiments, after obtaining the external parameters between the second device and the first device, the external parameter calibration device is based on the position and posture of the first device in the world coordinate system, and the relationship between the second device and the first device. The external parameter obtains the third calibration parameter, and the third calibration parameter is used to indicate the coordinate system conversion relationship between the second device and the world coordinate system. The third calibration parameter includes a rotation matrix between the coordinate system of the second device and the world coordinate system and a translation matrix between the coordinate system of the second device and the world coordinate system.

For example, the first device is a GNSS/IMU device, and the second device is a lidar. During the operation of the GNSS/IMU device, the absolute position and attitude of the origin of the GNSS/IMU device in the world coordinate system can be obtained. Based on equation (6), the coordinate system conversion relationship between the lidar and the world coordinate system is determined by the following equation (7).

The meaning of Equation (7) is, C _L through any point p _L and R _IW rotational transformation after translation transform T _IW, p _L of the same name can be obtained in the point C _W p _W in. C _L represents the coordinate system of the lidar, and C _W represents the world coordinate system. In equation (7), p _L represents a point, T _IW represents a position coordinate origin GNSS / IMU device in a world coordinate system of the coordinate system C _L lidar, R _IW represents GNSS / IMU device in the world coordinate system Stance. p _W represents a point in the world coordinate system.

It should be understood that this embodiment does not limit the time sequence between the three steps of S307, S308, and S309. In some embodiments, S307, S308, and S309 are executed sequentially. For example, execute S307 first, then execute S308, and then execute S309; another example, execute S308 first, then execute S309, and then execute S307; another example, execute S308 first, then execute S307, and then execute S309. In other embodiments, at least two of S307, S308, and S309 are executed in parallel, that is, at least two of S307, S308, and S309 are executed simultaneously.

It should be understood that this embodiment does not limit the timing of S301 and S303. In some embodiments, S301 and S303 can be executed sequentially. For example, S301 can be executed first, and then S303; or S303 can be executed first, and then S301. In other embodiments, S301 and S303 can also be executed in parallel, that is, S301 and S303 can be executed at the same time.

It should be understood that this embodiment does not limit the timing of S305 and S303. In some embodiments, S305 and S303 can be executed sequentially. For example, S305 can be executed first, and then S303; or S303 can be executed first, and then S305. In other embodiments, S305 and S303 can also be executed in parallel, that is, S305 and S303 can be executed simultaneously.

It should be understood that this embodiment only uses the same external parameter calibration device to perform the above S307 to S312 as an example for description. In some embodiments, the above S307 to S312 may be performed by multiple external parameter calibration devices in cooperation.

In the method provided in this embodiment, the first device is measured by the measuring device, the coordinate system conversion relationship between the measuring device and the first device is determined, and the measurement is performed by using at least one calibration plane of the measuring device and the second device. , Determine at least one plane group to which at least one calibration plane is respectively mapped under the coordinate system of the measuring device and the second device, and use the at least one plane group to determine the coordinate system conversion relationship between the measuring device and the second device. In this way, the coordinate system of the measuring device can be used as a relay between the coordinate system of the first device and the coordinate system of the second device to find the external parameters between the first device and the second device. Since the external parameters are obtained through the determined plane group, there is no need to extract the points with the same name from the point cloud data, thereby avoiding the influence of the extraction process of the points with the same name on the calibration accuracy, thereby improving the calibration accuracy. In addition, the method can be solidified into a computer automated execution process, avoiding the time-consuming and laborious problems caused by manual calculation of calibration parameters, thereby improving the calibration efficiency.

The method 300 is illustrated below by using the method 400 as an example. In method 400, the measuring device is a total station, the calibration plane is a calibration board, the first device is a GNSS/IMU device, the second device is a lidar, and the external parameter calibration device is a PC. In other words, the method flow described in the method 400 is about how to use the measurement data of the total station and the lidar on the calibration board on the PC to determine the external parameters between the lidar and the GNSS/IMU device.

Referring to FIG. 7, FIG. 7 is a flowchart of a method 400 for calibrating external parameters of lidar provided by an embodiment of the application. Exemplarily, the method 400 includes S401 to S404.

S401. The total station observes the marking points on the calibration board.

S402. The PC converts the observation result of the total station to the coordinate system of the GNSS/IMU device.

S403. Lidar scans the calibration board to obtain point cloud data.

In S404, the PC performs plane extraction and plane fitting based on the observation result of the total station and the point cloud data.

S405. The PC calculates the external parameters according to the fitted plane, thereby completing the external parameter calibration, and saves the determined external parameters to the external parameter file.

The method 300 or the method 400 of the embodiment of the present application is described above, and the external parameter calibration device of the embodiment of the present application is described below. It should be understood that the external parameter calibration device has any function of the external parameter calibration device in the above method 300 or method 400.

FIG. 8 is a schematic structural diagram of an external parameter calibration device 500 provided by an embodiment of the present application. As shown in FIG. 8, the device 500 includes: an acquisition module 501 for executing S307 and S312; and a determining module 502 for executing S308, S309, S310 and S311.

It should be understood that the apparatus 500 corresponds to the external parameter calibration equipment in the above method embodiment, and the modules in the apparatus 500 and the above-mentioned other operations and/or functions are used to implement the external parameter calibration equipment in the method 300 or the method 400, respectively. For the specific steps and methods, please refer to the method 300 or the method 400 mentioned above. For the sake of brevity, details are not repeated here.

It should be understood that when the device 500 is calibrating external parameters, only the division of the above-mentioned functional modules is used as an example. In practical applications, the above-mentioned function allocation can be completed by different functional modules as required, that is, the internal structure of the device 500 is divided into Different functional modules to complete all or part of the functions described above. In addition, the device 500 provided in the foregoing embodiment belongs to the same concept as the foregoing method 300 or method 400, and its specific implementation process is detailed in the method 300 or method 400, which will not be repeated here.

Corresponding to the method embodiments and virtual device embodiments provided in this application, the embodiments of this application also provide an external parameter calibration device. The hardware structure of the external parameter calibration device will be introduced below.

The external parameter calibration device 600 corresponds to the external parameter calibration device or PC in the above method 300 or method 400. The hardware, modules and the above-mentioned other operations and/or functions in the external parameter calibration device 600 are used to implement the external parameter calibration in the method embodiment. The various steps and methods implemented by the device or PC, and the detailed process of how the external parameter calibration device 600 calibrates the external parameters, can refer to the above method 300 or method 400 for specific details, and will not be repeated here for brevity. Wherein, the steps of the method 300 or the method 400 are completed by hardware integrated logic circuits in the processor of the external parameter calibration device 600 or instructions in the form of software. The steps of the method disclosed in the embodiments of the present application may be directly embodied as being executed and completed by a hardware processor, or executed and completed by a combination of hardware and software modules in the processor. The software module can be located in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, or electrically erasable programmable memory, registers. The storage medium is located in the memory, and the processor reads the information in the memory, and completes the steps of the above method in combination with its hardware. In order to avoid repetition, it will not be described in detail here.

The external parameter calibration device 600 corresponds to the external parameter calibration device 500 described above, and each functional module in the device 500 is implemented by the software of the external parameter calibration device 600. In other words, the functional modules included in the apparatus 500 are generated after the processor of the external parameter calibration device 600 reads the program code stored in the memory.

Referring to FIG. 9, FIG. 9 shows a schematic structural diagram of an external parameter calibration device 600 provided by an exemplary embodiment of the present application. For example, the external parameter calibration device 600 may be a host, a server, or a personal computer. The external parameter calibration device 600 can be implemented by a general bus architecture.

The external parameter calibration device 600 includes at least one processor 601, a communication bus 602, a memory 603, and at least one communication interface 604.

The processor 601 may be a general-purpose central processing unit (CPU), a network processor (NP), a microprocessor, or may be one or more integrated circuits used to implement the solutions of the present application, for example , Application-specific integrated circuit (ASIC), programmable logic device (programmable logic device, PLD) or a combination thereof. The above-mentioned PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a general array logic (generic array logic, GAL), or any combination thereof.

The communication bus 602 is used to transfer information between the aforementioned components. The communication bus 602 can be divided into an address bus, a data bus, a control bus, and so on. For ease of presentation, only one thick line is used in FIG. 9, but it does not mean that there is only one bus or one type of bus.

The memory 603 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, or it can be a random access memory (RAM) or can store information and instructions Other types of dynamic storage devices can also be electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disk storage , CD storage (including compressed CDs, laser disks, CDs, digital universal CDs, Blu-ray CDs, etc.), disk storage media or other magnetic storage devices, or can be used to carry or store desired program codes in the form of instructions or data structures And any other media that can be accessed by the computer, but not limited to this. The memory 603 may exist independently and is connected to the processor 601 through the communication bus 602. The memory 603 may also be integrated with the processor 601.

The communication interface 604 uses any device such as a transceiver for communicating with other devices or a communication network. The communication interface 604 includes a wired communication interface, and may also include a wireless communication interface. Among them, the wired communication interface may be, for example, an Ethernet interface. The Ethernet interface can be an optical interface, an electrical interface, or a combination thereof. The wireless communication interface may be a wireless local area network (WLAN) interface, a cellular network communication interface, or a combination thereof.

In a specific implementation, as an embodiment, the processor 601 may include one or more CPUs, such as CPU0 and CPU1 shown in FIG. 9.

In a specific implementation, as an embodiment, the external parameter calibration device 600 may include multiple processors, such as the processor 601 and the processor 605 shown in FIG. 9. Each of these processors can be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). The processor here may refer to one or more devices, circuits, and/or processing cores for processing data (such as computer program instructions).

In a specific implementation, as an embodiment, the external parameter calibration device 600 may further include an output device and an input device. The output device communicates with the processor 601 and can display information in a variety of ways. For example, the output device may be a liquid crystal display (LCD), a light emitting diode (LED) display device, a cathode ray tube (CRT) display device or a projector (projector), etc. The input device communicates with the processor 601 and can receive user input in a variety of ways. For example, the input device can be a mouse, a keyboard, a touch screen device, or a sensor device.

In some embodiments, the memory 603 is used to store the program code 610 for executing the solution of the present application, and the processor 601 can execute the program code 610 stored in the memory 603. That is, the external parameter calibration device 600 can implement the external parameter calibration method provided by the method embodiment through the processor 601 and the program code 610 in the memory 603.

The external parameter calibration device 600 in the embodiment of the present application may correspond to the external parameter calibration device in the above-mentioned method embodiments, and the processor 601, the communication interface 604, etc. in the external parameter calibration device 600 can implement the above-mentioned method embodiments The functions and/or various steps and methods implemented by the external reference calibration equipment in the. For the sake of brevity, I will not repeat them here.

It should be understood that the acquiring module 501 and the determining module 502 in the apparatus 500 are equivalent to the processor 601 or the processor 605 in the external parameter calibration device 600.

It should be understood that the above-mentioned external parameter calibration devices of various product forms respectively have any function of the external parameter calibration device in the above method embodiment, and will not be repeated here.

Those of ordinary skill in the art may realize that, in combination with the method steps and units described in the embodiments disclosed in this document, they can be implemented by electronic hardware, computer software, or a combination of both, in order to clearly illustrate the possibilities of hardware and software. Interchangeability. In the above description, the steps and compositions of the embodiments have been described generally in terms of functions. Whether these functions are executed by hardware or software depends on the specific application and design constraint conditions of the technical solution. A person of ordinary skill in the art may use different methods for each specific application to implement the described functions, but such implementation should not be considered as going beyond the scope of the present application.

Those skilled in the art can clearly understand that, for the convenience and conciseness of description, the specific working process of the above-described system, device, and module can be referred to the corresponding process in the foregoing method embodiment, which will not be repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed system, device, and method can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the modules is only a logical function division, and there may be other divisions in actual implementation, for example, multiple modules or components may be combined or may be Integrate into another system, or some features can be ignored or not implemented. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or modules, and may also be electrical, mechanical or other forms of connection.

The modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, that is, they may be located in one place, or they may be distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the objectives of the solutions of the embodiments of the present application.

In addition, the functional modules in the various embodiments of the present application may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or software function modules.

If the integrated module is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application is essentially or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium It includes several instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (read-only memory, ROM), random access memory (random access memory, RAM), magnetic disk or optical disk and other media that can store program code .

In this application, the terms "first", "second" and other words are used to distinguish the same or similar items with basically the same function and function. It should be understood that there is no logic or sequence between "first" and "second" The dependence relationship on the above does not limit the quantity and execution order. It should also be understood that although the following description uses the terms first, second, etc. to describe various elements, these elements should not be limited by the terms. These terms are only used to distinguish one element from another. For example, without departing from the scope of the various described examples, the first calibration parameter may be referred to as the second calibration parameter, and similarly, the second calibration parameter may be referred to as the first calibration parameter. Both the first calibration parameter and the second calibration parameter may be calibration parameters, and in some cases, may be separate and different calibration parameters.

The term "at least one" in this application means one or more, and the term "multiple" in this application means two or more than two, for example, multiple calibration planes means two or more Calibration plane.

It should also be understood that the term "if" can be interpreted to mean "when" ("when" or "upon") or "in response to determination" or "in response to detection." Similarly, depending on the context, the phrase "if it is determined..." or "if [the stated condition or event] is detected" can be interpreted to mean "when determining..." or "in response to determining..." "Or "when [stated condition or event] is detected" or "in response to detecting [stated condition or event]".

The above descriptions are only specific implementations of this application, but the protection scope of this application is not limited to this. Any person skilled in the art can easily think of various equivalent modifications within the technical scope disclosed in this application. Or replacement, these modifications or replacements should be covered within the scope of protection of this application. Therefore, the protection scope of this application shall be subject to the protection scope of the claims.

In the above-mentioned embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented by software, it can be implemented in the form of a computer program product in whole or in part. The computer program product includes one or more computer program instructions. When the computer program instructions are loaded and executed on the computer, the processes or functions in the embodiments of the present application are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer program instructions can be passed from a website, computer, server, or data center. Wired or wireless transmission to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or data center integrated with one or more available media. The usable medium may be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a digital video disc (DVD), or a semiconductor medium (for example, a solid-state hard disk), etc.

Those of ordinary skill in the art can understand that all or part of the steps in the foregoing embodiments can be implemented by hardware, or by a program instructing relevant hardware to be completed. The program can be stored in a computer-readable storage medium, as mentioned above. The storage medium can be read-only memory, magnetic disk or optical disk, etc.

The above descriptions are only optional embodiments of this application and are not intended to limit this application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included in the protection scope of this application within.

Claims

An external parameter calibration method, characterized in that the method includes:

Acquiring a first calibration parameter according to the measurement data of the first device by the measuring device, where the first calibration parameter is used to indicate the coordinate system conversion relationship between the measuring device and the first device;

Determine at least one first plane mapped by the at least one calibration plane in the coordinate system of the measuring device according to the measurement data of the at least one calibration plane by the measuring device;

Determine, according to the measurement data of the at least one calibration plane by the second device, at least one second plane mapped by the at least one calibration plane in the coordinate system of the second device;

According to the at least one first plane and the at least one second plane, at least one plane group is determined, the plane group includes a first plane and a second plane, and the first plane in the plane group corresponds to the second plane ；

Determining a second calibration parameter according to the at least one plane group, where the second calibration parameter is used to indicate a coordinate system conversion relationship between the measuring device and the second device;

Obtain an external parameter between the second device and the first device according to the first calibration parameter and the second calibration parameter.
The method according to claim 1, wherein the determining the second calibration parameter according to the at least one plane group comprises:

According to the at least one plane group, the first plane and the second plane in the plane group satisfy the matching condition, and the second calibration parameter is determined.
The method according to claim 2, wherein the first plane and the second plane in the plane group satisfy a matching condition, comprising:

The normal vector angle between the first plane and the second plane in the plane group is the smallest.
The method according to claim 3, wherein the second calibration parameter includes a rotation matrix, and the method is based on the at least one plane group and the method between the first plane and the second plane in the plane group. The vector angle is the smallest, and the second calibration parameter is determined, including:

The rotation matrix is determined according to the at least one plane group and the first optimization function, and the rotation matrix makes the value of the first optimization function a minimum value.
The method according to any one of claims 1 to 4, wherein the first plane and the second plane in the plane group satisfy a matching condition, comprising:

The distance between the first plane and the second plane in the plane group is the smallest.
The method according to claim 5, wherein the second calibration parameter includes a translation matrix, and the distance between the first plane and the second plane in the plane group is based on the at least one plane group Minimum, determine the second calibration parameters, including:

The translation matrix is determined according to the at least one plane group and the second optimization function, and the translation matrix makes the value of the second optimization function a minimum value.
The method according to any one of claims 1 to 6, wherein the second calibration parameter comprises a translation matrix, and the determining the second calibration parameter according to the at least one plane group comprises:

Using the rotation matrix and the initial translation matrix to perform rotation transformation and translation transformation on a point on the first plane to obtain a projection point of the point;

According to the at least one plane group, an initial translation matrix that minimizes the distance between the projection point and the second plane is determined as the translation matrix.
The method according to claim 1, wherein the acquiring the first calibration parameter according to the measurement data of the first device by the measuring device comprises:

According to the coordinate value of the mark point on the first device in the coordinate system of the first device and the coordinate value of the mark point measured by the measuring device in the coordinate system of the measuring device, obtain all Describe the first calibration parameter.
The method according to claim 1, wherein the measurement device is a total station, a laser scanner or a photogrammetric system, the calibration plane is a calibration board or a wall, and the first device is an inertial navigation device, A vehicle or a first lidar, and the second device is a second lidar, millimeter wave or camera.
An external parameter calibration device, characterized in that the device comprises:

An acquiring module, configured to acquire a first calibration parameter according to the measurement data of the first device by the measuring device, where the first calibration parameter is used to indicate the coordinate system conversion relationship between the measuring device and the first device;

A determining module, configured to determine at least one first plane mapped by the at least one calibration plane in the coordinate system of the measuring device according to the measurement data of the at least one calibration plane by the measuring device;

A determining module, configured to determine at least one second plane mapped by the at least one calibration plane in the coordinate system of the second device according to the measurement data of the at least one calibration plane by the second device;

A determining module, configured to determine at least one plane group according to the at least one first plane and the at least one second plane, the plane group including a first plane and a second plane, the first plane in the plane group Corresponding to the second plane;

A determining module, configured to determine a second calibration parameter according to the at least one plane group, where the second calibration parameter is used to indicate a coordinate system conversion relationship between the measuring device and the second device;

The acquiring module is further configured to acquire external parameters between the second device and the first device according to the first calibration parameter and the second calibration parameter.
The device according to claim 10, wherein the determining module is configured to determine the second calibration parameter according to the at least one plane group, the first plane and the second plane in the plane group satisfy a matching condition .
The device according to claim 11, wherein the first plane and the second plane in the plane group satisfy a matching condition, comprising: a normal vector between the first plane and the second plane in the plane group The angle is the smallest.
The device according to claim 12, wherein the second calibration parameter comprises a rotation matrix, and the determining module is configured to determine the rotation matrix according to the at least one plane group and the first optimization function, so The rotation matrix makes the value of the first optimization function a minimum value.
The device according to any one of claims 10-13, wherein the first plane and the second plane in the plane group satisfy a matching condition, comprising: the first plane and the second plane in the plane group The distance between them is the smallest.
The device according to claim 14, wherein the second calibration parameter comprises a translation matrix, and the determining module is configured to determine the translation matrix according to the at least one plane group and a second optimization function, so The translation matrix makes the value of the second optimization function the minimum value.
The device according to any one of claims 10 to 15, wherein the second calibration parameter comprises a translation matrix, and the determining module is configured to use the rotation matrix and the initial translation matrix to compare the first plane Perform rotation transformation and translation transformation on the point on the above to obtain the projection point of the point; according to the at least one plane group, determine the initial translation matrix that minimizes the distance between the projection point and the second plane, as the The translation matrix.
The apparatus according to claim 10, wherein the acquisition module is configured to obtain a coordinate value of the marker point on the first device in the coordinate system of the first device and the measurement device measured by the measurement device. The coordinate values of the marker points in the coordinate system of the measuring device are obtained, and the first calibration parameters are acquired.
The apparatus according to claim 10, wherein the measuring equipment is a total station, a laser scanner or a photogrammetric system, the calibration plane is a calibration board or a wall, and the first equipment is an inertial navigation equipment, A vehicle or a first lidar, and the second device is a second lidar, millimeter wave or camera.
An external parameter calibration device, characterized in that the external parameter calibration device comprises a processor, and the processor is used to execute instructions so that the external parameter calibration device executes any one of claims 1 to 9 The method described.
A computer-readable storage medium, wherein at least one instruction is stored in the storage medium, and the instruction is read by a processor to make an external parameter calibration device execute any one of claims 1 to 9 The method described.