Radar and inertial navigation equipment calibration evaluation method, device, equipment and medium

Abstract

The invention provides a radar and inertial navigation equipment calibration evaluation method and device, equipment and a medium, and the method comprises the steps: obtaining initial intersection points of at least two targets and the ground, the initial intersection points being determined based on a target point cloud which is collected by a target radar of a target vehicle and is related to a preset area; the initial intersection point is registered with reference intersection points corresponding to the at least two targets respectively, target external parameters between the target radar and the vehicle-end inertial navigation equipment are determined, calibration between the target radar and the vehicle-end inertial navigation equipment is completed, and the reference intersection points are determined based on the vehicle-end inertial navigation equipment; projecting the target point cloud based on the target external parameters, and determining target intersection points of the at least two targets and the ground; and evaluating a calibration result based on an error between the target intersection point and the reference intersection point. Through the error between the initial intersection point between the target radar and the target and the target intersection point, the quantitative evaluation of the radar calibration result is realized.

Description

Technical Field

[0001] This application relates to the technical field of radar calibration, and more specifically, to an evaluation method, device, equipment, and medium for calibrating a radar and an inertial navigation device. Background Art

[0002] Radar calibration refers to precisely calibrating a radar to ensure its ability to accurately measure the distance, angle, and position of a target object. Radar calibration is a very important part of intelligent driving technology, which directly affects the measurement accuracy and reliability of the radar.

[0003] In the prior art, there are many ways to calibrate a radar, such as static calibration, dynamic calibration, multi-sensor fusion calibration, etc. However, after calibrating the radar, it is not easy to understand the accuracy of the calibration result. To ensure the normal use of the radar, it is necessary to evaluate the calibration result of the radar. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide an evaluation method, device, equipment, and medium for calibrating a radar and an inertial navigation device to overcome the problems in the prior art.

[0005] In a first aspect, an embodiment of this application provides an evaluation method for calibrating a radar and an inertial navigation device, and the method includes:

[0006] Obtain the initial intersection points of at least two targets with the ground respectively, where the initial intersection points are determined based on the target point cloud of a preset area collected by a target radar of a target vehicle;

[0007] Register the initial intersection points with the reference intersection points corresponding to the at least two targets respectively to determine the target external parameters between the target radar and the vehicle-mounted inertial navigation device, and complete the calibration between the target radar and the vehicle-mounted inertial navigation device, where the reference intersection points are determined based on the vehicle-mounted inertial navigation device;

[0008] Project the target point cloud based on the target external parameters to determine the target intersection points of the at least two targets with the ground respectively;

[0009] Evaluate the calibration result based on the error between the target intersection points and the reference intersection points.

[0010] In some technical solutions of this application, the above target includes a first panel and a second panel at a preset angle; the obtaining of the initial intersection points of at least two targets with the ground respectively includes:

[0011] Based on the target point cloud, determine the first panel point cloud and the second panel point cloud corresponding to the first panel and the second panel respectively;

[0012] Determine the panel intersection line of the first panel point cloud and the second panel point cloud;

[0013] Based on the panel intersection line, determine the initial intersection position where the target intersects the ground.

[0014] In some technical solutions of the present application, the above reference intersection position is determined in the following manner:

[0015] Obtain the initial measurement positions corresponding to the at least two targets collected by the measurement device;

[0016] Through the vehicle-mounted inertial navigation device, determine the ground UTM pose of the ground in the UTM coordinate system;

[0017] Based on the ground UTM pose, determine the reference intersection position of the initial measurement position in the ground coordinate system.

[0018] In some technical solutions of the present application, the above registration of the initial intersection position with the reference intersection positions corresponding to the at least two targets to determine the target extrinsic parameters between the target radar and the vehicle-mounted inertial navigation device includes:

[0019] Determine the registration transformation matrix by registering the initial intersection position and the reference intersection position;

[0020] Based on the registration transformation matrix and the initial extrinsic parameters of the target radar, obtain the target extrinsic parameters.

[0021] In some technical solutions of the present application, the first panel point cloud and the second panel point cloud corresponding to the first panel and the second panel respectively are obtained in the following manner:

[0022] Based on the initial extrinsic parameters of the target radar, convert the target point cloud into a converted point cloud;

[0023] According to the preset height requirement, screen the converted point cloud to obtain a candidate point cloud;

[0024] Calculate the actual ground normal vector of the candidate point cloud;

[0025] Based on the difference between the actual ground normal vector and the ideal ground normal vector, determine the preliminary adjustment extrinsic parameters corresponding to the candidate point cloud;

[0026] Based on the preliminary adjustment extrinsic parameters, iteratively adjust the candidate point cloud until the ground height of the adjusted candidate point cloud is less than the preset target height threshold to determine the adjustment extrinsic parameters of the target radar;

[0027] Process the target point cloud based on the adjusted extrinsic parameters to obtain the first panel point cloud corresponding to the first panel and the second panel point cloud corresponding to the second panel.

[0028] In a second aspect, an embodiment of the present application provides an evaluation device for calibrating a radar and an inertial navigation device. The device includes:

[0029] An acquisition module, configured to acquire initial intersection points of at least two targets with the ground respectively, where the initial intersection points are determined based on target point clouds of a preset area collected by a target radar of a target vehicle;

[0030] A registration module, configured to register the initial intersection points with reference intersection points corresponding to the at least two targets respectively to determine target extrinsic parameters between the target radar and the vehicle-mounted inertial navigation device, and complete the calibration between the target radar and the vehicle-mounted inertial navigation device, where the reference intersection points are determined based on the vehicle-mounted inertial navigation device;

[0031] A projection module, configured to project the target point cloud based on the target extrinsic parameters to determine target intersection points of the at least two targets with the ground respectively;

[0032] An evaluation module, configured to evaluate the calibration result based on the error between the target intersection points and the reference intersection points.

[0033] In some technical solutions of the present application, the above target includes a first panel and a second panel at a preset angle; to acquire the initial intersection points of at least two targets with the ground respectively, the acquisition module is configured to:

[0034] Based on the target point cloud, determine a first panel point cloud and a second panel point cloud corresponding to the first panel and the second panel respectively;

[0035] Determine the panel intersection line of the first panel point cloud and the second panel point cloud;

[0036] Based on the panel intersection line, determine the initial intersection points where the target intersects with the ground.

[0037] In some technical solutions of the present application, the above registration module determines the reference intersection points in the following manner:

[0038] Acquire initial measurement points corresponding to the at least two targets respectively collected by a measurement device;

[0039] Through the vehicle-mounted inertial navigation device, determine the ground UTM pose in the UTM coordinate system;

[0040] Based on the ground UTM pose, determine the reference intersection points of the initial measurement points in the ground coordinate system.

[0041] In a third aspect, an embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned method for evaluating the calibration of a radar and an inertial navigation device are implemented.

[0042] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, the steps of the above-mentioned method for evaluating the calibration of a radar and an inertial navigation device are executed.

[0043] The technical solutions provided by the embodiments of the present application may include the following beneficial effects:

[0044] The method of the present application includes obtaining initial intersection points of at least two targets with the ground respectively, where the initial intersection points are determined based on target point clouds of a preset area collected by a target radar of a target vehicle; registering the initial intersection points with reference intersection points respectively corresponding to the at least two targets to determine a target extrinsic parameter between the target radar and an in-vehicle inertial navigation device, and completing the calibration between the target radar and the in-vehicle inertial navigation device, where the reference intersection points are determined based on the in-vehicle inertial navigation device; projecting the target point clouds based on the target extrinsic parameter to determine target intersection points of the at least two targets with the ground respectively; and evaluating the calibration result based on the error between the target intersection points and the reference intersection points.

[0045] The present application realizes a quantitative evaluation of the radar calibration result through the error between the initial intersection points and the target intersection points between the target radar and the target.

[0046] To make the above objects, features, and advantages of the present application more obvious and understandable, the following specific preferred embodiments are given, and in conjunction with the accompanying drawings, the detailed description is as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] To more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0048] Figure 1 A schematic flowchart of a method for evaluating the calibration of a radar and an inertial navigation device provided by an embodiment of the present application is shown;

[0049] Figure 2Shows a schematic diagram of a target provided by an embodiment of the present application;

[0050] Figure 3 Shows a schematic diagram of an evaluation device for calibrating a radar and an inertial navigation device provided by an embodiment of the present application;

[0051] Figure 4 Is a schematic structural diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0052] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. It should be understood that the accompanying drawings in the present application are only for the purposes of illustration and description, and are not used to limit the protection scope of the present application. In addition, it should be understood that the schematic drawings are not drawn to actual scale. The flowcharts used in the present application illustrate operations implemented according to some embodiments of the present application. It should be understood that the operations in the flowchart may not be implemented in sequence, and steps without logical context may be reversed or implemented simultaneously. In addition, those skilled in the art may add one or more other operations to the flowchart or remove one or more operations from the flowchart under the guidance of the content of the present application.

[0053] In addition, the described embodiments are only some embodiments of the present application, rather than all embodiments. The components of the embodiments of the present application usually described and illustrated in the accompanying drawings here may be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application claimed, but merely represents selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative efforts fall within the protection scope of the present application.

[0054] It should be noted that the term "including" will be used in the embodiments of the present application to indicate the existence of the features stated thereafter, but does not exclude adding other features.

[0055] Common radar and inertial navigation calibration methods in the prior art include:

[0056] Static calibration: This is the simplest calibration method. By fixing the Lidar and the inertial navigation system on the same plane, a series of data points are collected, and then an optimization algorithm is used to estimate the external parameters between the Lidar and the inertial navigation system.

[0057] Dynamic calibration: This method requires calibration during motion. By fixing the Lidar and inertial navigation system on the same moving platform and collecting data at different poses and positions. By analyzing the collected data, the external parameters between the Lidar and the inertial navigation system can be obtained.

[0058] Point cloud registration: This method registers the point cloud data collected by the Lidar with the pose data provided by the inertial navigation system. By using registration algorithms such as ICP (Iterative Closest Point), the point cloud data is aligned with the pose data, thereby obtaining the external parameters between the Lidar and the inertial navigation system.

[0059] Multi-sensor fusion: This method uses data from multiple sensors (such as GPS, gyroscopes, accelerometers, etc.) for fusion, and estimates the external parameters between the Lidar and the inertial navigation system through optimization algorithms. This method can improve the accuracy and robustness of calibration.

[0060] In the prior art, there are some drawbacks in the process of calibrating Lidar and inertial navigation. The following are some potential problems of various methods:

[0061] Static calibration: It is necessary to fix the Lidar and the inertial navigation system on the same plane, and sometimes there may be limitations on the installation position and pose. For complex motions, poses or position changes, static calibration may not provide accurate results.

[0062] Dynamic calibration: Dynamic calibration needs to be carried out during motion, which may require higher technical requirements and equipment support. There may be uncertainties during the motion process, such as vibrations, dynamic changes, etc., and these factors may affect the accuracy of the calibration results.

[0063] Point cloud registration: Point cloud registration algorithms are sensitive to the accuracy and noise of data, and noise and inaccurate data may lead to inaccurate registration results. The registration algorithm may require a long calculation time, especially for large-scale point cloud data.

[0064] Multi-sensor fusion: The multi-sensor fusion method requires data from multiple sensors, which may require more complex hardware configurations and data processing flows. There may be difficulties in time synchronization and data alignment between different sensors.

[0065] The above methods are all methods that cannot quantitatively evaluate the calibration accuracy.

[0066] Based on this, the embodiments of the present application provide an evaluation method, device, equipment and medium for calibrating radar and inertial navigation equipment, which will be described below through embodiments.

[0067] Figure 1The flowchart of an evaluation method for calibrating a radar and an inertial navigation device provided by an embodiment of the present application is shown, where the method includes steps S101 - S104; specifically:

[0068] S101. Obtain the initial intersection points of at least two targets with the ground respectively, where the initial intersection points are determined based on the target point cloud of a preset area collected by a target radar of a target vehicle;

[0069] S102. Register the initial intersection points with the reference intersection points corresponding to the at least two targets respectively to determine the target external parameters between the target radar and the vehicle - end inertial navigation device, and complete the calibration between the target radar and the vehicle - end inertial navigation device, where the reference intersection points are determined based on the vehicle - end inertial navigation device;

[0070] S103. Project the target point cloud based on the target external parameters to determine the target intersection points of the at least two targets with the ground respectively;

[0071] S104. Evaluate the calibration result based on the error between the target intersection points and the reference intersection points.

[0072] The present application realizes the quantitative evaluation of the radar calibration result through the error between the initial intersection points and the target intersection points between the target radar and the target.

[0073] Some embodiments of the present application will be described in detail below. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0074] Before introducing the radar calibration method in the embodiments of the present application, the application scenario of the embodiments of the present application will be introduced first. The radar here is the radar on the target vehicle, for example, it can be a low - beam radar, etc. A low - beam lidar usually adopts a fixed - type lidar, and only a few laser beams are emitted from the radar scanning head. Once the laser beam touches an object, it will be reflected from the object and form a point cloud on the radar scanning head receiver. Its principle is similar to that of a monocular camera, and 3D information is obtained through multiple 2D images.

[0075] When calibrating the above - mentioned radar, the embodiments of the present application need to use such as Figure 2The target shown here. The target includes panel 1 and panel 2, and panel 1 and panel 2 are connected by a rotatable device, that is, the angle between panel 1 and panel 2 is adjustable. The angle between panel 1 and panel 2 can be adjusted according to actual measurement needs. In the embodiments of the present application, either of panel 1 and panel 2 can be used as the first panel, and the other as the second panel. In a specific embodiment, the target can be a PVC hard panel with a length of 120 cm and a height of 80 cm. The target can be placed 7-8 meters in front of the radar. It can be understood that in actual operation, panels of different sizes and / or different materials can be selected according to requirements. After setting up the target, start calibrating the radar on the vehicle.

[0076] S101. Obtain at least two initial intersection points of the targets with the ground respectively, where the initial intersection points are determined based on the target point cloud of a preset area collected by the target radar of the target vehicle.

[0077] The vehicle in the embodiments of the present application is an intelligent driving vehicle. The vehicle to be calibrated is called the target vehicle, and the radar set on the target vehicle is called the target radar. The target radar can perform point cloud collection. The point cloud collected by the target radar in the embodiments of the present application is called the target point cloud. Since the embodiments of the present application need to use the target to calibrate the radar, the target should be set at a position where the target radar can collect it. That is to say, the target point cloud collected by the target radar contains the point cloud of the target.

[0078] When determining the initial intersection points, it includes: obtaining the target point cloud of a preset area collected by the target radar of the target vehicle, where a preset number of targets are set in the preset area, and the target includes a first panel and a second panel at a preset angle;

[0079] Based on the target point cloud, determine the first panel point cloud corresponding to the first panel and the second panel point cloud corresponding to the second panel;

[0080] Based on the panel intersection line of the first panel point cloud and the second panel point cloud, determine the initial intersection points of the target with the ground.

[0081] After obtaining the target point cloud collected by the target radar, the embodiments of the present application also need to screen out the first panel point cloud of the first panel and the second panel point cloud of the second panel from the target point cloud. The screening process: filter the target point cloud to obtain the remaining point cloud, and then cluster the remaining point cloud to obtain the first panel point cloud corresponding to the first panel and the second panel point cloud corresponding to the second panel.

[0082] Specifically, the process of obtaining the first panel point cloud corresponding to the first panel and the second panel point cloud corresponding to the second panel is as follows: Based on the initial extrinsic parameters of the target radar, the target point cloud is converted into a transformed point cloud; according to the preset height requirements, the transformed point cloud is filtered to obtain a candidate point cloud; the actual ground normal vector of the candidate point cloud is calculated; based on the difference between the actual ground normal vector and the ideal ground normal vector, the preliminary adjusted extrinsic parameters corresponding to the candidate point cloud are determined; based on the preliminary adjusted extrinsic parameters, the candidate point cloud is iteratively adjusted until the ground height of the adjusted candidate point cloud is less than the preset target height threshold to determine the adjusted extrinsic parameters of the target radar; based on the adjusted extrinsic parameters, the target point cloud is processed to obtain the first panel point cloud corresponding to the first panel and the second panel point cloud corresponding to the second panel.

[0083] Among them, the preset height requirements here include the requirement of being less than the first height threshold and the requirement of being within the first height interval. The first height threshold is determined based on the initial extrinsic parameters of the target radar and the ground; the first height interval is determined based on the height information of the primary selected point cloud. That is, the filtering of the transformed point cloud is to filter out the point cloud that is both less than the first height threshold and within the first height interval from the transformed point cloud as the candidate point cloud.

[0084] The above-mentioned adjusted extrinsic parameters include the adjusted roll angle, the adjusted pitch angle, and the adjusted height. The adjusted roll angle and the adjusted pitch angle are determined based on the actual ground normal vector and the ideal ground normal vector; the adjusted height is calculated based on the adjusted roll angle and the adjusted pitch angle to adjust the candidate point cloud so that the angle between the adjusted candidate point cloud and the ground is less than the preset angle threshold.

[0085] When the above analysis process is specifically implemented, it can refer to the method shown in Figure 3 : The target point cloud is converted from the target radar coordinate system to the ground coordinate system. The specific conversion method is: The target point cloud is subjected to coordinate conversion according to the initial extrinsic parameters of the target radar to obtain the transformed point cloud in the ground coordinate system (i.e., the base ground coordinate system). The initial extrinsic parameters here can be determined during the production process of the target vehicle, which represents the relative position relationship between the radar and the ground after the production of the target vehicle. For example, according to the initial extrinsic parameter T1_guess of the target radar, the target point cloud P1_lidar1 is converted to the transformed point cloud P1_base-ground in the ground coordinate system: P1_base-ground = T1_guess * P1_lidar1.

[0086] After obtaining the transformed point cloud, it is necessary to exclude the height outliers in the transformed point cloud to obtain the candidate point cloud. Here, the basis for excluding the height outliers are the first height threshold requirement and the first height interval requirement respectively. In the embodiment of the present application, it is considered that the point cloud greater than or equal to the height threshold is the outlier point cloud. Therefore, it is necessary to exclude the point cloud exceeding the height threshold from the transformed point cloud to obtain the preliminary selected point cloud with a height less than the height threshold. After obtaining the preliminary selected point cloud, it is also necessary to screen the preliminary selected point cloud again. The screening of the preliminary selected point cloud is based on the height interval, and the point cloud not in the height interval in the preliminary selected point cloud is excluded, and the point cloud in the height interval is used as the candidate point cloud.

[0087] In a specific embodiment, the first height threshold can be determined based on the initial extrinsic parameters of the target radar. For example, multiply the initial extrinsic parameters of the target radar by a preset extrinsic parameter magnification factor to obtain the first height threshold. Sort the transformed point cloud P1_base - ground by height z, and obtain the points (preliminary selected point cloud) less than 1.5 times (preset extrinsic parameter magnification factor) of the initial extrinsic parameter T1_guess.

[0088] In a specific embodiment, the first height interval can be determined based on the height information of each preliminary selected point cloud. For example, calculate the average height of each preliminary selected point cloud, add and subtract a preset height to the average height respectively to obtain the height interval. Calculate the average value of z, and use z average value ± 10 cm (preset height) as the candidate point cloud.

[0089] After obtaining the candidate point cloud, calculate the actual ground normal vector of the candidate point cloud. For example, solve the actual ground normal vector normal1_svd of the candidate point cloud through SVD. Calculate the difference between the actual ground normal vector and the ideal ground normal vector (for example, the normal vector is (0, 0, 1)), and convert the difference into a roll angle and a pitch angle. Based on the roll angle and the pitch angle, adjust the candidate point cloud so that the angle between the adjusted candidate point cloud and the ground is less than a preset angle threshold; calculate the ground height h1_svd of the adjusted candidate point cloud from the ground; use the roll angle, the pitch angle, and the ground height as the preliminary adjusted extrinsic parameters. Based on the preliminary adjusted extrinsic parameters, iteratively adjust the candidate point cloud until the ground height of the adjusted candidate point cloud is less than a preset target height threshold to determine the adjusted extrinsic parameters of the target radar. Here, the target height threshold is set based on the actual height of the ground. The ground height of the adjusted point cloud being less than the preset target height threshold indicates that the actual ground normal vector of the candidate point cloud coincides with or is close to (the difference is small and can be ignored) the ideal ground normal vector, or it can be understood that the candidate point cloud coincides with the actual ground.

[0090] After that, the adjusted candidate point cloud is screened again through the second height interval, and the non-ground point cloud is obtained from the candidate point cloud. In the embodiment of the present application, it is considered that the points in the second height interval in the candidate point cloud are the ground point cloud. After excluding the ground point cloud in the candidate point cloud, the non-ground point cloud in the candidate point cloud can be obtained. Here, the second height interval is determined based on the adjusted external parameters of the target radar. That is, by adding and subtracting a preset height to and from the adjusted external parameters of the target radar respectively, the second height interval can be obtained.

[0091] In specific implementation, SVD (Singular Value Decomposition) is used to solve the actual ground normal vector normal1_svd and height h1_svd of the candidate point cloud. Based on the actual ground normal vector normal1_svd and the ideal ground normal vector normal_ground (0, 0, 1), the difference is calculated, and the difference is converted into the roll angle roll1 and pitch angle pitch1. The adjusted variables of the roll angle roll and pitch angle pitch are calculated, and the ground point cloud is adjusted using the variables to make the ground point cloud conform to the real ground. The average height H1_ground - everage of the converted ground point cloud is calculated, and the lidar height ground height H1_fix = -H1_ground - everage is obtained. The adjusted roll1, pitch1 and H1_fix are used as the adjusted external parameter T1_plane - fit for backflow to adjust the input point cloud until the adjusted value of H1_fix is less than 0.5 cm. (Pre - process the point cloud based on the adjusted external parameter T1_plane - fit and perform transformation to make the point cloud more parallel to the ground. A new adjusted external parameter T1_plane - fit will be optimized in each iteration). After the ground plane correction, part of the point cloud is filtered out from the target point cloud to obtain the remaining point cloud. In specific implementation, the filtered - out point cloud is generally the point cloud 10 cm above the ground and the point cloud 10 cm below the ground.

[0092] The remaining point cloud obtained contains the target point cloud and other point clouds, so it is also necessary to obtain the target point cloud from the remaining point cloud.

[0093] In order to obtain the target point cloud, the embodiment of the present application performs clustering processing on the remaining point cloud. In specific implementation, the distance - based clustering method dbscan can be selected. The remaining point cloud is processed through the dbscan algorithm to obtain the target point cloud. Since the target in the embodiment of the present application includes the first panel and the second panel, after obtaining the target point cloud, it is also necessary to distinguish the first panel point cloud of the first panel and the second panel point cloud of the second panel.

[0094] After obtaining the first panel point cloud and the second panel point cloud, it is also necessary to determine the panel intersection line between the first panel point cloud and the second panel point cloud. The panel intersection line is determined based on the intersection line vector and the intersection point of the first panel and the second panel. To determine the panel intersection line, it is necessary to determine the intersection line vector not only according to the first normal vector of the first panel and the second normal vector of the second panel, but also to determine the intersection point of the first panel and the second panel according to the first plane equation and the second plane equation.

[0095] Regarding determining the intersection line vector: Use the Ransac algorithm to fit the target point cloud, and extract the respective normal vectors of the two planes in the target, denoted as Normal1 and Normal2. Normal1 cross Normal2 = Normal_line, and Normal_line is the direction of the panel intersection line vector. Among them, Normal_line.x, Normal_line.y, and Normal_line.z respectively represent the component magnitudes of the intersection line vector in the x, y, and z dimensions.

[0096] Regarding determining the intersection point position of the first panel and the second panel: The first plane equation is plane_equation1, and the second plane equation is plane_equation2. Construct an augmented matrix from the two plane equations, and use Gaussian elimination on the augmented matrix to obtain the intersection point position P_cross of the two planes, where P_cross.x, P_cross.y, and P_cross.z respectively represent the x, y, and z coordinate values of this point.

[0097] After determining the intersection line vector and the intersection point of the first panel and the second panel, the embodiments of the present application can determine the panel intersection line. When determining the panel intersection line, the embodiments of the present application need to determine the transformation ratio based on the coordinate components of the intersection line vector along the preset direction and the coordinate values of the intersection point in the preset direction, and then determine the panel intersection line according to the transformation ratio and the line segment model.

[0098] In specific implementation, the transformation ratio t = (0 - P_cross.z) / Normal_line.z. Then, through the transformation ratio t, substitute it into the line segment formula to obtain the x and y positions of the point where the panel intersection line is at a height of 0, denoted as P_x and P_y. Combine P_x, P_y, and 0 to obtain the position P_target of the intersection point of the target and the ground.

[0099] S102. Register the initial intersection point position with the reference intersection point positions respectively corresponding to the at least two targets to determine the target external parameters between the target radar and the vehicle-end inertial navigation device, and complete the calibration between the target radar and the vehicle-end inertial navigation device, where the reference intersection point positions are determined based on the vehicle-end inertial navigation device.

[0100] The reference intersection points corresponding to the targets here are determined by the points marked by the marking device when placing the targets. For example, when placing the targets, a compass is used to make a mark at the center position of the target. The point marked on a certain target indicates the corresponding relationship between the point and the target. In the embodiments of the present application, the points marked by the marking device on the target are called initial measurement points. After obtaining the initial measurement points, the reference intersection points can be obtained by converting the coordinate system of the test measurement points.

[0101] Specifically, the coordinate system conversion is as follows: obtain the initial measurement points corresponding to the at least two targets collected by the measurement device; determine the ground UTM pose of the ground in the UTM coordinate system through the vehicle-mounted inertial navigation device; based on the ground UTM pose, determine the reference intersection points of the initial measurement points in the ground coordinate system.

[0102] In specific implementation, through the vehicle-mounted inertial navigation device INS, obtain the utm pose of the current base_ground, denoted as T_utm_bg. Through the pose of the base_ground in utm, transfer the compass marking coordinates (P_SN1, P_SN2, P_SN3, P_SN4, and P_SN5) to the base_ground coordinate system to obtain the observations of the compass in the base_ground coordinate system, denoted as P_SN1_bg, P_SN2_bg, P_SN3_bg, P_SN4_bg, and P_SN5_bg.

[0103] After determining the intersection points and the corresponding reference intersection points, a registration algorithm can be used to process the two to obtain a registration transformation matrix. Combine the registration transformation matrix with the initial transformation matrix of the target radar relative to the ground to achieve the registration of the target radar. For example, use ICP to register the two sets of obtained observation points, and the transformation matrix T_resdiual is obtained from the registration result. The final extrinsic parameter between the lidar and the ins is T_final = T_resdiual * T_guess.

[0104] S103. Based on the target extrinsic parameter, project the target point cloud to determine the target intersection points of the at least two targets with the ground respectively.

[0105] After calibrating the target radar and the inertial navigation device in the above manner, the embodiments of the present application also need to evaluate the calibration result to ensure the calibration accuracy.

[0106] By calibrating the target radar and inertial navigation equipment, the external target parameters between the target radar and the inertial navigation equipment can be obtained. In the embodiment of the present application, the target point cloud collected by the target radar is projected based on the external target parameters. By performing the projection, the target intersection points of each target with the ground are determined. For example, the updated positions after projection are denoted as P_final_target1, P_final_target2, P_final_target3, P_final_target4, and P_final_target5.

[0107] S104. Evaluate the calibration result based on the error between the target intersection point and the reference intersection point.

[0108] After obtaining the target intersection points, the distance difference between the target intersection points and the reference intersection points is calculated to judge the quality of the calibration result. The larger the distance difference between the target intersection points and the reference intersection points, the worse the calibration result. On the contrary, the smaller the distance difference between the target intersection points and the reference intersection points, the better the calibration result.

[0109] In specific implementation, a distance threshold can be set according to actual working needs. The calibration result with the distance difference between the target intersection point and the reference intersection point greater than the distance threshold is determined to be unqualified and needs to be recalibrated; the calibration result with the distance difference between the target intersection point and the reference intersection point less than or equal to the distance threshold is determined to be qualified and can be used normally.

[0110] Figure 3 The structural schematic diagram of an evaluation device for calibrating a radar and an inertial navigation device provided by an embodiment of the present application is shown. The device includes:

[0111] An acquisition module, configured to acquire the initial intersection points of at least two targets with the ground respectively, where the initial intersection points are determined based on the target point cloud of a preset area collected by the target radar of the target vehicle;

[0112] A registration module, configured to register the initial intersection points with the reference intersection points corresponding to the at least two targets respectively, determine the external target parameters between the target radar and the vehicle-end inertial navigation equipment, and complete the calibration between the target radar and the vehicle-end inertial navigation equipment, where the reference intersection points are determined based on the vehicle-end inertial navigation equipment;

[0113] A projection module, configured to project the target point cloud based on the external target parameters, and determine the target intersection points of the at least two targets with the ground respectively;

[0114] An evaluation module, configured to evaluate the calibration result based on the error between the target intersection point and the reference intersection point.

[0115] The target includes a first panel and a second panel at a preset angle; the obtaining of at least two initial intersection points of the targets with the ground respectively includes:

[0116] Based on the target point cloud, determining a first panel point cloud and a second panel point cloud corresponding to the first panel and the second panel respectively;

[0117] Determining the panel intersection line of the first panel point cloud and the second panel point cloud;

[0118] Based on the panel intersection line, determining the initial intersection points where the target intersects with the ground.

[0119] The reference intersection points are determined by the following method:

[0120] Obtaining the initial measurement points corresponding to the at least two targets collected by the measurement device;

[0121] Determining the ground UTM pose in the UTM coordinate system through the vehicle-mounted inertial navigation device;

[0122] Based on the ground UTM pose, determining the reference intersection points of the initial measurement points in the ground coordinate system.

[0123] The registering of the initial intersection points with the reference intersection points corresponding to the at least two targets respectively to determine the target external parameters between the target radar and the vehicle-mounted inertial navigation device includes:

[0124] Determining a registration transformation matrix by registering the initial intersection points and the reference intersection points;

[0125] Based on the registration transformation matrix and the initial external parameters of the target radar, obtaining the target external parameters.

[0126] The determining of the first panel point cloud and the second panel point cloud corresponding to the first panel and the second panel respectively based on the target point cloud includes:

[0127] Performing ground correction on the target point cloud, filtering out some point clouds in the target point cloud to obtain a remaining point cloud;

[0128] Performing clustering processing on the remaining point cloud to obtain the first panel point cloud corresponding to the first panel and the second panel point cloud corresponding to the second panel.

[0129] Such as Figure 4As shown in the figure, an embodiment of the present application provides an electronic device for implementing the evaluation method for calibrating a radar and an inertial navigation device in the present application. The device includes a memory, a processor, a bus, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned evaluation method for calibrating a radar and an inertial navigation device are implemented.

[0130] Specifically, the above-mentioned memory and processor can be general-purpose memory and processor, which are not specifically limited here. When the processor runs the computer program stored in the memory, it can execute the above-mentioned evaluation method for calibrating a radar and an inertial navigation device.

[0131] Corresponding to the evaluation method for calibrating a radar and an inertial navigation device in the present application, an embodiment of the present application also provides a computer-readable storage medium. A computer program is stored on the computer-readable storage medium, and when the computer program is run by a processor, the steps of the above-mentioned evaluation method for calibrating a radar and an inertial navigation device are executed.

[0132] Specifically, the storage medium can be a general-purpose storage medium, such as a removable disk, a hard disk, etc. When the computer program on the storage medium is run, it can execute the above-mentioned evaluation method for calibrating a radar and an inertial navigation device.

[0133] In the embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. The system embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some communication interfaces. The indirect couplings or communication connections of the systems or units can be in electrical, mechanical or other forms.

[0134] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units. They can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0135] In addition, the functional units in the embodiments provided in the present application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0136] When the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0137] It should be noted that: similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. In addition, the terms "first", "second", "third", etc. are only used for descriptive distinction and cannot be understood as indicating or implying relative importance.

[0138] Finally, it should be noted that: the above-mentioned embodiments are only specific implementation manners of this application, used to illustrate the technical solutions of this application, rather than limiting it. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: any person skilled in the art within the technical scope disclosed in this application can still modify the technical solutions recorded in the foregoing embodiments, or can easily think of changes, or perform equivalent replacements on some of the technical features; and these modifications, changes, or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. An evaluation method for calibrating a radar and an inertial navigation device, characterized in that, the method includes: Obtain the initial intersection points of at least two targets with the ground respectively, where the initial intersection points are determined based on the target point cloud of a preset area collected by a target radar of a target vehicle; Register the initial intersection points with the reference intersection points corresponding to the at least two targets respectively to determine the target external parameters between the target radar and the vehicle-mounted inertial navigation device, and complete the calibration between the target radar and the vehicle-mounted inertial navigation device, where the reference intersection points are determined based on the vehicle-mounted inertial navigation device; Based on the target external parameters, project the target point cloud to determine the target intersection points of the at least two targets with the ground respectively; Evaluate the calibration result based on the error between the target intersection points and the reference intersection points.

2. The method according to claim 1, characterized in that, the target includes a first panel and a second panel at a preset angle; the obtaining of the initial intersection points of at least two targets with the ground respectively includes: Based on the target point cloud, determine the first panel point cloud and the second panel point cloud corresponding to the first panel and the second panel respectively; Determine the panel intersection line of the first panel point cloud and the second panel point cloud; Based on the panel intersection line, determine the initial intersection points where the target intersects with the ground.

3. The method according to claim 1, characterized in that, the reference intersection points are determined by the following method: Obtain the initial measurement points corresponding to the at least two targets collected by a measurement device; Through the vehicle-mounted inertial navigation device, determine the ground UTM pose in the UTM coordinate system; Based on the ground UTM pose, determine the reference intersection points of the initial measurement points in the ground coordinate system.

4. The method according to claim 1, characterized in that, the registering of the initial intersection points with the reference intersection points corresponding to the at least two targets respectively to determine the target external parameters between the target radar and the vehicle-mounted inertial navigation device includes: Determine the registration transformation matrix by registering the initial intersection points and the reference intersection points; Based on the registration transformation matrix and the initial external parameters of the target radar, obtain the target external parameters.

5. The method according to claim 2, characterized in that, the first panel point cloud and the second panel point cloud corresponding to the first panel and the second panel respectively are obtained by the following method: Based on the initial external parameters of the target radar, convert the target point cloud into a converted point cloud; According to the preset height requirement, screen the converted point cloud to obtain a candidate point cloud; Calculate the actual ground normal vector of the candidate point cloud; Based on the difference between the actual ground normal vector and the ideal ground normal vector, determine the preliminary adjustment external parameters corresponding to the candidate point cloud; Based on the preliminary adjustment external parameters, iteratively adjust the candidate point cloud until the ground height of the adjusted candidate point cloud is less than the preset target height threshold to determine the adjusted external parameters of the target radar. Process the target point cloud based on the adjusted extrinsic parameters to obtain the first panel point cloud corresponding to the first panel and the second panel point cloud corresponding to the second panel.

6. An evaluation device for calibrating a radar and an inertial navigation device, characterized in that the device includes: an acquisition module, configured to acquire initial intersection positions of at least two targets with the ground respectively, where the initial intersection positions are determined based on target point clouds of a preset area collected by a target radar of a target vehicle; a registration module, configured to register the initial intersection positions with reference intersection positions corresponding to the at least two targets respectively to determine target extrinsic parameters between the target radar and the vehicle-mounted inertial navigation device, and complete the calibration between the target radar and the vehicle-mounted inertial navigation device, where the reference intersection positions are determined based on the vehicle-mounted inertial navigation device; a projection module, configured to project the target point cloud based on the target extrinsic parameters to determine target intersection positions of the at least two targets with the ground respectively; an evaluation module, configured to evaluate the calibration result based on the error between the target intersection positions and the reference intersection positions.

7. The device according to claim 6, characterized in that the target includes a first panel and a second panel at a preset angle; to acquire initial intersection positions of at least two targets with the ground respectively, the acquisition module is configured to: determine a first panel point cloud and a second panel point cloud corresponding to the first panel and the second panel respectively based on the target point cloud; determine a panel intersection line of the first panel point cloud and the second panel point cloud; determine the initial intersection position where the target intersects with the ground based on the panel intersection line.

8. The device according to claim 6, characterized in that the registration module determines the reference intersection positions in the following manner: acquire initial measurement positions corresponding to the at least two targets respectively collected by a measurement device; determine the ground UTM pose of the ground in the UTM coordinate system through the vehicle-mounted inertial navigation device; determine the reference intersection positions of the initial measurement positions in the ground coordinate system based on the ground UTM pose.

9. An electronic device, characterized in that it includes: a processor, a memory and a bus, where the memory stores machine-readable instructions executable by the processor. When the electronic device runs, the processor communicates with the memory through the bus, and when the machine-readable instructions are executed by the processor, the steps of the evaluation method for calibrating a radar and an inertial navigation device according to any one of claims 1 to 7 are executed.

10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is run by a processor, the steps of the evaluation method for calibrating a radar and an inertial navigation device according to any one of claims 1 to 7 are executed.

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