Laser radar debugging method, device and equipment, storage medium and product

Abstract

The invention discloses a laser radar debugging method and device, equipment, a storage medium and a product, and the method comprises the steps: enabling a laser radar and a reflecting plate to be located at different test distances through controlling the relative movement of the laser radar and the reflecting plate, testing the distance measurement capability of the laser radar in each view field region at each test distance, and achieving the debugging of the laser radar. Under the condition that the distance measuring capability of the edge field-of-view area and the distance measuring capability of the center field-of-view area differ greatly, the detection signal intensity of the laser radar for the edge field-of-view area is adjusted, and the distance measuring capability difference of the laser radar for each field-of-view area is reduced, so that the probability that the tracking trajectory of the target jumps or is discontinuous is reduced. And the use effect of the laser radar is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of lidar, and specifically, to a lidar debugging method, device, equipment, storage medium and product. Background Art

[0002] Currently, lidar performance testing mostly adopts an overall testing method, that is, the debugging work is carried out only based on the overall test results. However, this testing method has obvious defects and cannot effectively guarantee the performance balance of the lidar in different field-of-view regions. Therefore, after debugging, the lidar may have a large gap between the ranging ability of the edge and the ranging ability of the central field-of-view region.

[0003] This performance difference will bring serious problems to moving target tracking. In practical applications, when the target is in different field-of-view regions of the lidar, due to the large difference in ranging ability between the edge and the center, the tracking trajectory of the target will appear jumpy or discontinuous, which greatly affects the use effect of the lidar in scenarios such as autonomous driving and robot navigation. Summary of the Invention

[0004] Based on this, the present invention provides a lidar debugging method, device, equipment, storage medium and product, which can analyze the ranging ability of the lidar for different field-of-view regions, adjust the detection signal intensity of the detector for different field-of-view regions when the ranging ability of the field-of-view regions varies greatly, reduce the probability of jumpy or discontinuous tracking trajectories, and improve the use effect of the lidar.

[0005] To achieve the above object, an embodiment of the present invention provides a lidar debugging method, including:

[0006] Controlling the relative movement of the lidar and the reflector to different test distances;

[0007] At each of the test distances, controlling the lidar to turn on the shooting mode, collecting the detection point cloud data projected by the lidar on the reflector in different field-of-view regions, and obtaining the total number of theoretical points of the lidar falling on the reflector in each field-of-view region; wherein, the overall field-of-view of the lidar is divided into several of the field-of-view regions, and the field-of-view regions include a central field-of-view region and several edge field-of-view regions;

[0008] Determining the ranging upper limit value of the lidar for each of the field-of-view regions based on the detection point cloud data and the total number of theoretical points of each of the field-of-view regions at each of the test distances;

[0009] Adjust the detection signal intensity of the lidar for the field of view area to be debugged, so as to reduce the difference between the ranging upper limit value of the lidar for the field of view area to be debugged and the ranging upper limit value of the lidar for the central field of view area; wherein, the field of view area to be debugged is the marginal field of view area where the difference between the ranging upper limit value and the ranging upper limit value corresponding to the central field of view area is greater than the set ranging difference threshold.

[0010] To achieve the above object, an embodiment of the present invention further provides a lidar debugging device, including:

[0011] A movement control module, configured to control the relative movement of the lidar and the reflector to different test distances;

[0012] A detection module, configured to, at each of the test distances, control the lidar to turn on the shooting mode, collect the detection point cloud data projected by the lidar on the reflector in different field of view areas, and obtain the total number of theoretical points that fall on the reflector within each field of view area of the lidar; wherein, the overall field of view of the lidar is divided into several field of view areas, and the field of view areas include a central field of view area and several marginal field of view areas;

[0013] A performance calculation module, configured to determine the ranging upper limit value of the lidar for each of the field of view areas based on the detection point cloud data and the total number of theoretical points of each of the field of view areas at each of the test distances;

[0014] A debugging module, configured to adjust the detection signal intensity of the lidar for the field of view area to be debugged, so as to reduce the difference between the ranging upper limit value of the lidar for the field of view area to be debugged and the ranging upper limit value of the lidar for the central field of view area; wherein, the field of view area to be debugged is the marginal field of view area where the difference between the ranging upper limit value and the ranging upper limit value corresponding to the central field of view area is greater than the set ranging difference threshold.

[0015] To achieve the above object, an embodiment of the present invention further provides a lidar debugging device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the lidar debugging method as described in any of the above embodiments.

[0016] To achieve the above object, an embodiment of the present invention further provides a computer-readable storage medium, which includes a stored computer program. When the computer program runs, it controls the device where the computer-readable storage medium is located to execute the lidar debugging method as described in any of the above embodiments.

[0017] To achieve the above object, an embodiment of the present invention further provides a computer program product, including a computer program / instructions, and when the computer program / instructions are executed by a processor, the lidar debugging method described in any of the above embodiments is implemented.

[0018] Compared with the prior art, the lidar debugging method, device, equipment, storage medium and product disclosed in the embodiments of the present invention first control the relative movement of the lidar and the reflector to different test distances; then, at each of the test distances, control the lidar to turn on the shooting mode, collect the detection point cloud data projected by the lidar on the reflector in different field-of-view regions, and obtain the total number of theoretical points of the lidar falling on the reflector in each field-of-view region; wherein, the overall field of view of the lidar is divided into several field-of-view regions, and the field-of-view regions include a central field-of-view region and several edge field-of-view regions; then, determine the ranging upper limit value of the lidar for each of the field-of-view regions based on the detection point cloud data and the total number of theoretical points of each of the field-of-view regions at each of the test distances; finally, adjust the detection signal intensity of the lidar for the field-of-view region to be debugged to reduce the difference degree between the ranging upper limit value of the lidar for the field-of-view region to be debugged and the ranging upper limit value of the lidar for the central field-of-view region; wherein, the field-of-view region to be debugged is an edge field-of-view region where the difference degree between the ranging upper limit value and the ranging upper limit value corresponding to the central field-of-view region is greater than the set ranging difference threshold. It can be seen that in the embodiments of the present invention, by controlling the relative movement of the lidar and the reflector, the lidar and the reflector are at different test distances, and the ranging ability of the lidar for each field-of-view region is tested at each test distance. When the ranging ability of the edge field-of-view region and the central field-of-view region differs greatly, the detection signal intensity of the lidar for the edge field-of-view region is adjusted to reduce the gap in the ranging ability of the lidar for each field-of-view region, thereby reducing the probability that the tracking trajectory of the target jumps or is discontinuous and improving the use effect of the lidar. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the present invention, the drawings required for the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1 is a schematic flow chart of a lidar debugging method provided by an embodiment of the present invention;

[0021] Figure 2 is a schematic structural diagram of a lidar debugging device provided by an embodiment of the present invention;

[0022] Figure 3 It is a schematic structural diagram of a lidar debugging device provided by an embodiment of the present invention. Specific embodiments

[0023] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0024] See Figure 1 , which is a schematic flowchart of a lidar debugging method provided by an embodiment of the present invention.

[0025] Specifically, the lidar debugging method includes steps S1 to S4:

[0026] S1. Control the relative movement of the lidar and the reflector to different test distances;

[0027] S2. At each of the test distances, control the lidar to turn on the shooting mode, collect the detection point cloud data projected by the lidar on the reflector in different field-of-view regions, and obtain the total number of theoretical points of the lidar falling on the reflector in each field-of-view region; wherein, the overall field of view of the lidar is divided into several of the field-of-view regions, and the field-of-view regions include a central field-of-view region and several edge field-of-view regions;

[0028] S3. Determine the ranging upper limit value of the lidar for each of the field-of-view regions based on the detection point cloud data and the total number of theoretical points of each of the field-of-view regions at each of the test distances;

[0029] S4. Adjust the detection signal intensity of the lidar for the field-of-view region to be debugged to reduce the difference between the ranging upper limit value of the lidar for the field-of-view region to be debugged and the ranging upper limit value of the lidar for the central field-of-view region; wherein, the field-of-view region to be debugged is an edge field-of-view region where the difference between the ranging upper limit value and the ranging upper limit value corresponding to the central field-of-view region is greater than the set ranging difference threshold.

[0030] It should be noted that lidar is a radar system that detects the position, speed and other characteristic quantities of targets by emitting laser beams. Lidar can be applied to devices such as vehicles and drones. For example, vehicle-mounted lidar, also known as vehicle-mounted three-dimensional laser scanner, is a mobile three-dimensional laser scanning system installed on a vehicle. It mainly consists of a transmitting system, a receiving system and an information processing system. It uses laser beams to scan the surrounding environment to obtain high-precision three-dimensional point cloud data, helping the vehicle perceive the shape and distance information of the surrounding environment. And with the booming development of autonomous driving technology, the installation rate of vehicle-mounted lidar is gradually increasing. It is expected that the pre-installed market of vehicle-mounted lidar in China will exceed 42 million units in 2030.

[0031] Specifically, considering that there are test errors between different field-of-view regions (such as the edge region and the central region) caused by the optical system, detector sensitivity, and environmental factor interference, resulting in inaccurate and incomplete test results, and the lidar cannot be debugged in a timely and effective manner, affecting the subsequent use effect of the lidar. In this embodiment, the overall field of view of the lidar is divided into multiple field-of-view regions. For example, the field of view angle is evenly divided into 9 field-of-view regions. The middle field-of-view region is the central field-of-view region, and the other field-of-view regions are the edge field-of-view regions. The lidar and the reflector are controlled to move relative to each other to different test distances. At different test distances, the lidar is controlled to rotate relative to the reflector to detect the corresponding field-of-view regions, and the ranging ability of the lidar for each field-of-view region at each test distance is determined according to the detection results, so as to determine the detection upper limit value of the lidar for each field-of-view region. Among them, the detection upper limit value is the maximum detection distance at which the ranging ability of the lidar meets the minimum accuracy requirement. Then, the difference in the detection ability between each field-of-view region of the lidar is analyzed. When the difference in the detection upper limit value between the edge field-of-view region and the central field-of-view region of the lidar is relatively large, the detection signal intensity of the lidar for the edge field-of-view region is adjusted to narrow the difference in the detection upper limit value between the edge field-of-view region and the central field-of-view region of the lidar.

[0032] Preferably, before adjusting the detection signal intensity of the lidar for the edge field-of-view region, it is necessary to ensure that the detection upper limit value of the lidar for each field-of-view region is greater than the preset ranging requirement threshold. The specific value of the preset ranging requirement threshold is set according to the actual situation and is not limited here. Or, when adjusting the detection signal intensity of the lidar for the edge field-of-view region, the detection signal intensity of the lidar for the central field-of-view region can also be adjusted synchronously to ensure that the detection upper limit value of the lidar for each field-of-view region is greater than the preset ranging requirement threshold.

[0033] Compared with the prior art, in the embodiment of the present invention, by controlling the relative movement between the lidar and the reflector, the lidar and the reflector are at different test distances, and the ranging ability of the lidar for each field of view area is tested at each test distance. When the ranging ability difference between the edge field of view area and the central field of view area is large, the detection signal intensity of the lidar for the edge field of view area is adjusted to narrow the gap in the ranging ability of the lidar for each field of view area, thereby reducing the probability that the tracking trajectory of the target jumps or is discontinuous, and improving the use effect of the lidar.

[0034] In a preferred embodiment, determining the ranging upper limit value of the lidar for each of the field of view areas based on the detected point cloud data and the total number of theoretical points at each of the test distances includes:

[0035] Based on the detected point cloud data, determining the total number of valid points of the lidar for each of the field of view areas at each of the test distances, and calculating the detection success rate of the lidar for each of the field of view areas at each of the test distances based on the total number of valid points and the total number of theoretical points;

[0036] For the first field of view area, the maximum test distance with the detection success rate greater than the preset ratio threshold is used as the ranging upper limit value of the lidar for the first field of view area; wherein, the first field of view area is any one of all the field of view areas.

[0037] It should be noted that the total number of valid points refers to the number of points that the detector of the lidar actually receives and can accurately identify as coming from the reflector during the actual test. In actual situations, due to the influence of various factors, such as the scattering of laser light, the uneven reflectivity of the reflector, environmental noise, and the sensitivity of the detector, not all points that should theoretically fall on the reflector can be accurately detected and identified. The total number of valid points is obtained by analyzing and processing the actually collected data, and only those points that meet certain conditions (such as the signal intensity exceeding the threshold, the distance measurement being within a reasonable range, etc.) are regarded as valid points. The total number of theoretical points refers to the number of points that should theoretically be detected and fall on the reflector within the field of view area, based on the scanning principle and geometric model of the lidar; it is usually calculated through a mathematical model according to parameters such as the field of view angle of the lidar, the scanning frequency, the size and position of the reflector, and the distance between the lidar and the reflector. This number is the theoretical value in an ideal situation without considering any actual factor influence, and it provides a benchmark for evaluating the performance of the lidar.

[0038] Exemplarily, the upper limit value of the ranging for each field of view area of the lidar is obtained through the following steps: 1. The field of view angle of the vehicle-mounted lidar is evenly divided into 9 field of view areas, and the system automatically moves the turntable carrying the reflector to the preset lower limit of the test distance. 2. The system automatically moves the turntable carrying the vehicle-mounted lidar into the i-th (i = 1, 2,..., 9) field of view area. 3. The vehicle-mounted lidar turns on the shooting mode and automatically obtains and generates a point cloud PCD data file. 4. Analyze the PCD data file, and calculate the total number of theoretical points nr and the total number of valid points ne that fall on the reflector in the current field of view area. 5. Calculate the POD value (i.e., the detection success rate, also expressed as the ranging ability) of the current field of view area through the formula POD = (ne / nr) * 100%. 6. Determine whether the current position of the turntable carrying the reflector is between the lower limit and the upper limit of the test distance. If so, go to step 7; if not, go to step 8. 7. The turntable carrying the reflector continues to move forward 1 m (the specific moving step size can be set according to the actual situation), and repeat steps 3 to 6. 8. Output the POD values calculated at each moving distance in the current field of view area, calculate and compare and output the current distance value Di (i = 1, 2,..., 9) when POD > the preset ratio threshold (such as 50%, 60% or 80%, etc.). Di represents the distance value of the i-th field of view area. That is, the maximum distance value Di when POD > the preset ratio threshold is used as the upper limit value of the ranging for the i-th field of view area. 9. Determine whether the serial number of the current field of view area is less than 9. If so, repeat steps 2 to 8; if not, go to step 10. 10. Output the distance Di (i = 1, 2,..., 9) values calculated for the 9 field of view areas respectively, select the minimum value among them and compare it with the preset evaluation standard value. If it is greater, it means the test passes, and the result is automatically output to the test report.

[0039] In a preferred embodiment, the detection signal intensity of the lidar for the field of view area to be debugged is adjusted in the following manner:

[0040] Taking the test distance as the independent variable and the detection success rate of the lidar for the central field of view area as the dependent variable, a fitting formula is generated;

[0041] Input the upper limit value of the ranging of the lidar for the field of view area to be debugged into the fitting formula to obtain the target detection success rate;

[0042] Based on the preset corresponding relationship between the detection signal intensity of the lidar for the field of view area to be debugged and the detection success rate associated with the upper limit value of the ranging, calculate the target signal intensity according to the target detection success rate;

[0043] Adjust the detection signal intensity of the lidar for the field of view area to be debugged so that the signal intensity of the lidar for the field of view area to be debugged is the target signal intensity.

[0044] Exemplarily, after steps 1 to 10 in the previous embodiment, the detection signal intensity of the lidar for the field of view area to be debugged is adjusted through the following steps: 11. Calculate the ranging ability difference percentage between the edge field of view area and the central field of view area through the formula ΔE = (Di - D5) |D5 * 100%; where D5 is the upper ranging limit value of the central field of view area. 12. If the absolute value of ΔE is less than or equal to the set ranging difference threshold (such as 5%, 6% or 8%, etc.), it means that the ranging abilities of the edge field of view area and the central field of view area are not very different, which may be caused by environmental interference or distortion in the edge area. At this time, the distance value Di measured in the edge field of view area can be error-corrected based on the set ranging difference threshold. For example, a 5% error correction is made to the distance value Di measured in the edge field of view area. That is, if ΔE is positive, the actual ranging ability distance value Di of the edge field of view area 修正 = Di 原始 - Di 原始 * 0.05, otherwise the actual ranging ability distance value Di of the edge field of view area 修正 = Di 原始 + Di 原始 * 0.05. 13. If the absolute value of ΔE is greater than the set ranging difference threshold, it means that the ranging abilities of the edge field of view area and the central field of view area are very different, which may be due to the large change in the detector sensitivity under different fields of view. At this time, gain compensation needs to be performed on the signal intensity of the detector in the corresponding field of view area. 14. According to the data set corresponding to the position information of the central field of view area and the POD value obtained in step 7, the parameter values of a0, a1,..., an can be calculated using the polynomial fitting algorithm y = a0 + a1 * x + a2 * x2 + … + an * xn (where x represents the position information and y represents the POD). 15. Substitute the distance Di of the edge field of view area as the x parameter into the polynomial fitting formula in step 14, and the corrected POD value of the edge field of view area (i.e., the target detection success rate POD 校正 ) can be calculated. If POD 校正 - POD 原始 > 0, it means that the signal intensity of the detector in this field of view area needs to be amplified, otherwise it means that the signal intensity of the detector needs to be reduced; where POD 原始Refers to the detection success rate calculated based on the total number of valid points and the total number of theoretical points. 16. Use data-driven polynomial fitting modeling to construct the relationship between signal strength and POD (POD(S) = a*S^2 + b*S + c). The coefficients a, b, and c can be obtained through the POD and signal strength S within the marginal field of view area's ranging ability. The corrected POD is: POD 校正 = a*(S 原始 + ΔS) 2 + b*S 原始 + c, and the signal adjustment amount can be calculated S 原始 Refers to the detection signal strength before adjustment. 17. After performing ΔS gain compensation on the detector in the marginal field of view area, repeat steps 2 - 11. 18. If the absolute value of the ranging ability deviation ΔE between the marginal field of view area and the central field of view area is less than or equal to the set ranging difference threshold, process according to step 12. 19. If the absolute value of the ranging ability deviation ΔE between the marginal field of view area and the central field of view area exceeds the set ranging difference threshold, continue to repeat steps 13 - 16.

[0045] In a preferred embodiment, moving the lidar and the reflector relative to each other to different test distances includes:

[0046] Controlling the reflector to move to the test position through the control system to perform the lidar debugging method at the test position.

[0047] Further, before debugging, perform automatic calibration first. The process of automatic calibration is as follows:

[0048] Assume that the physical center of the vehicle-mounted lidar is used as the origin of a coordinate system, and its spatial coordinates are γ(0, 0, 0). The lidar emits a large number of laser beams in the direction of the reflector, and different-shaped visible patterns will be formed in the physical space according to the reflectivity of the irradiated object surface.

[0049] The system automatically captures the point cloud PCD data obtained by the vehicle-mounted lidar, filters out the valid point cloud data falling on the reflector according to the reflectivity of the reflector. After completing the automatic reflector detection, set the centroid of all the point clouds on the reflector as the center position of the reflector, and obtain the spatial coordinates of the center position of the reflector as γ(x, y, z).

[0050] To ensure that the center of the vehicle-mounted lidar is on the normal line of the center position of the reflector, it is necessary to calculate how the turntable carrying the vehicle-mounted lidar moves. The motion vector M = γ(x, y, z) - γ(0, 0, 0), and the motion components projected onto the Y-axis and Z-axis are d y = y - 0 and d z = z - 0.

[0051] The turntable equipped with an on-vehicle lidar automatically moves linearly left and right by d y and moves linearly up and down by d z so that the center of the on-vehicle lidar is exactly on the normal line of the center position of the reflector, and the automatic calibration of the center position is completed.

[0052] After the automatic detection and confirmation of the reflector in the second step, starting from the fact that a plane equation can be determined according to the formula Ax + By + Cz + D = 0, the normal vector n(A, B, C) of the plane can be obtained by importing the spatial position coordinate information of multiple points.

[0053] According to the formula the angle θ between the reflector plane and the X-axis of the on-vehicle lidar can be obtained x .

[0054] The turntable equipped with an on-vehicle lidar automatically rotates left and right by r x = 90° - θ x so that the signal emission surface of the on-vehicle lidar is parallel to the reflector plane, and the automatic calibration of the perpendicularity is completed.

[0055] In a preferred embodiment, it further includes:

[0056] Determining the valid points and the ranging values of the valid points in each of the field of view regions at the specified test distance position based on the detected point cloud data;

[0057] Calculating the average ranging value of the ranging values of all the valid points in the first field of view region;

[0058] Calculating the ranging accuracy of the first field of view region based on the ranging values of all the valid points and the average ranging value;

[0059] For the first field of view region, after squaring the difference between the ranging value of each valid point and the actual distance from the lidar to the test distance position and then performing a summation operation, an intermediate value is obtained; the flatness value is calculated according to the intermediate value and the number of valid points; wherein, the flatness value is positively correlated with the intermediate value, and the flatness value is negatively correlated with the number of valid points.

[0060] Exemplarily, the automatic test steps for the ranging accuracy and accuracy test items are as follows:

[0061] 1. Evenly divide the field of view angle of the on-vehicle lidar into 9 field of view regions, and the system automatically moves the turntable equipped with the reflector to the specified test distance position.

[0062] 2. The system automatically moves the turntable equipped with the on-vehicle lidar into the i-th (i = 1, 2,..., 9) field of view region.

[0063] 3. The vehicle-mounted lidar turns on the shooting mode and automatically obtains and generates a point cloud PCD data file.

[0064] 4. Analyze the PCD data file, obtain the number of valid points falling on the reflector within the field of view area, and equate the ranging value of each valid point to the vertical distance d1, d2,... d from the ranging center of the vehicle-mounted lidar to the reflector. n 。

[0065] 5. Through the formula where represents the average value of the vertical distances from the ranging center of the vehicle-mounted lidar to the reflector converted from n valid points, and d represents the actual distance from the ranging center of the vehicle-mounted lidar to the reflector, the ranging accuracy δ d value can be calculated.

[0066] 6. Through the formula where d i represents the vertical distance from the ranging center of the vehicle-mounted lidar to the reflector converted from the i-th valid point, and n represents the total number of selected valid points, the ranging precision σ d value can be calculated.

[0067] 7. Judge whether the current field of view area serial number is less than 9. If so, repeat steps 2 to 6. If not, output the ranging accuracies δ d and ranging precisions σ d calculated for the 9 field of view areas respectively, select the minimum value among them and compare it with the pre-set evaluation standard value. If both the ranging accuracy δ d and the ranging precision σ d are less than the corresponding evaluation standards, it means the test passes, and the result is automatically output to the test report.

[0068] Exemplarily, the automated test steps for the flatness test item are as follows:

[0069] 1. Divide the field of view angle of the vehicle-mounted lidar evenly into 9 field of view areas, and the system automatically moves the turntable carrying the reflector to the specified test distance position (the actual distance between the lidar and the emitter is L).

[0070] 2. The system automatically moves the turntable carrying the vehicle-mounted lidar into the i-th (1, 2,... 9) field of view area.

[0071] 3. The vehicle-mounted lidar turns on the shooting mode and automatically obtains and generates a point cloud PCD data file.

[0072] 4. Analyze the PCD data file, obtain the number of valid points within the field of view area that fall on the reflector, and equate the ranging value of each valid point to the vertical distance d1, d2, …… d from the ranging center of the vehicle-mounted lidar to the reflector. n 。

[0073] 5. Calculate r i =d i -L.

[0074] 6. Through the formula where n represents the number of selected valid points, the flatness value P can be calculated.

[0075] 7. Determine whether the current field of view area serial number is less than 9.

[0076] 8. If so, repeat steps 2 to 6.

[0077] 9. If not, output the flatness values P calculated for the 9 field of view areas respectively, select the minimum value among them and compare it with the preset judgment standard value. If it is less, it means the test passes, and the result is automatically output to the test report.

[0078] In a preferred embodiment, the method further includes:

[0079] Control the reflector to move to the specified test distance position;

[0080] At the specified test distance position, control the turntable carrying the lidar to rotate at a preset rotation step size, and at each rotation angle of the turntable carrying the lidar, control the lidar to turn on the shooting mode to collect the detection point cloud data projected onto the reflector at different rotation angles of the lidar as the field of view angle test point cloud data;

[0081] Determine the field of view angle performance of the lidar based on the field of view angle test point cloud data.

[0082] Exemplarily, the automatic test steps for the field of view angle test items are as follows:

[0083] 1. The system automatically moves the turntable carrying the reflector to the specified test distance position.

[0084] 2. The vehicle-mounted lidar turns on the shooting mode and automatically obtains the generated point cloud PCD data file.

[0085] 3. Analyze the PCD data file and check whether the number of valid points on the reflector under the current field of view is greater than 0.

[0086] 4. If so, the turntable carrying the vehicle-mounted lidar steps and rotates left at a preset rotation step size (such as 0.01°).

[0087] 5. Repeat steps 2, 3, and 4 above until the number of valid points on the reflector in the forward field of view is zero, and record the angle θ of the turntable carrying the vehicle-mounted lidar at this time. l 。

[0088] 6. The turntable carrying the vehicle-mounted lidar rotates step by step to the right with a preset rotation step size.

[0089] 7. Repeat steps 2, 3, and 6 above until the number of valid points on the reflector in the forward field of view is zero, and record the angle θ of the turntable carrying the vehicle-mounted lidar at this time. r 。

[0090] 8. Through the formula FOV h =|θ l -θ r |-β h , where β h represents the angular spread of the reflector relative to the lidar ranging center in the horizontal direction, and the field of view angle FOV in the horizontal direction can be calculated. h 。

[0091] 9. Similarly, the turntable carrying the vehicle-mounted lidar rotates step by step upward by 0.01°.

[0092] 10. Repeat steps 2, 3, and 9 above until the number of valid points on the reflector in the forward field of view is zero, and record the angle θ of the turntable carrying the vehicle-mounted lidar at this time. t 。

[0093] 11. The turntable carrying the vehicle-mounted lidar rotates step by step downward by 0.01°.

[0094] 12. Repeat steps 2, 3, and 11 above until the number of valid points on the reflector in the forward field of view is zero, and record the angle θ of the turntable carrying the vehicle-mounted lidar at this time. b 。

[0095] 13. Through the formula FOV v =|θ t -θ b |-β v , where β v represents the angular spread of the reflector relative to the lidar ranging center in the vertical direction, and the field of view angle FOV in the vertical direction can be calculated. v 。

[0096] 14. Compare the horizontal field of view angle FOV h and the vertical field of view angle FOV v obtained from the tests in step 8 and step 13 with the pre-set judgment standard values. If both are greater, it means the test passes, and the result is automatically output to the test report.

[0097] Compared with the prior art, in this embodiment, the reflector and the lidar are placed on the corresponding turntables. First, automatic calibration is performed. After the automatic calibration is completed, the distance between the lidar and the reflector is adjusted by the turntable, the rotation angle of the turntable carrying the lidar is adjusted, and the rotation angle of the lidar is adjusted (that is, the laser projected by the lidar onto the reflector through different field-of-view regions is adjusted). Then, under different states, the detection point cloud data is collected to test the ranging ability, ranging accuracy and precision, flatness, and field of view angle, and the detection signal intensity of the lidar for each field-of-view region is adjusted based on the ranging ability of the lidar for different field-of-view angles, so as to reduce the difference in the ranging ability of the lidar between the edge field-of-view region and the central field-of-view region, reduce the probability of the tracking trajectory jumping or being discontinuous, and improve the use effect of the lidar. The entire test process is completely automated without manual intervention by engineers, greatly reducing the complexity of the test and shortening the test time. At the same time, it supports automatic calibration of the positional relationship between the lidar and the reflector, making the signal emission surface of the lidar parallel to the reflector plane and the physical center point of the lidar on the normal line direction of the center point of the reflector plane, greatly reducing the calibration time and improving the work efficiency of test engineers.

[0098] See Figure 2 , the embodiment of the present invention further provides a lidar debugging device, including:

[0099] A movement control module 21, configured to control the relative movement of the lidar and the reflector to different test distances;

[0100] A detection module 22, configured to, at each of the test distances, control the lidar to turn on the shooting mode, collect the detection point cloud data projected by the lidar onto the reflector in different field-of-view regions, and obtain the total number of theoretical points of the lidar falling on the reflector in each field-of-view region; wherein, the overall field of view of the lidar is divided into several of the field-of-view regions, and the field-of-view regions include a central field-of-view region and several edge field-of-view regions;

[0101] A performance calculation module 23, configured to determine the ranging upper limit value of the lidar for each of the field-of-view regions based on the detection point cloud data and the total number of theoretical points of each of the field-of-view regions at each of the test distances;

[0102] A debugging module 24 is configured to adjust the detection signal intensity of the lidar for a field of view area to be debugged, so as to reduce the difference between the ranging upper limit value of the lidar for the field of view area to be debugged and the ranging upper limit value of the lidar for the central field of view area; wherein, the field of view area to be debugged is an edge field of view area where the difference between the ranging upper limit value and the ranging upper limit value corresponding to the central field of view area is greater than a set ranging difference threshold.

[0103] It should be noted that the specific working process of the lidar debugging device can refer to the working process of the lidar debugging method in the above embodiment, which will not be elaborated here.

[0104] Compared with the prior art, the lidar debugging device disclosed in the embodiment of the present invention controls the relative movement of the lidar and the reflector, so that the lidar and the reflector are at different test distances, and tests the ranging ability of the lidar for each field of view area at each test distance. When the ranging abilities of the edge field of view area and the central field of view area differ greatly, the detection signal intensity of the lidar for the edge field of view area is adjusted to reduce the gap in the ranging abilities of the lidar for each field of view area, thereby reducing the probability that the tracking trajectory of the target jumps or is discontinuous and improving the use effect of the lidar.

[0105] See Figure 3 , the embodiment of the present invention further provides a lidar debugging device, including a processor 31, a memory 32, and a computer program stored in the memory 32 and configured to be executed by the processor 31. When the processor 31 executes the computer program, the steps in the embodiment of the above lidar debugging method are implemented, such as Figure 1 the steps S1 to S4 described in

[0106] Exemplarily, the computer program can be divided into one or more modules. The one or more modules are stored in the memory 32 and executed by the processor 31 to complete the present invention. The one or more modules can be a series of computer program instruction segments capable of performing specific functions, and these instruction segments are used to describe the execution process of the computer program in the lidar debugging device. For example, the computer program can be divided into multiple modules, and the specific functions of each module are as follows:

[0107] A movement control module 21 is configured to control the relative movement of the lidar and the reflector to different test distances;

[0108] The detection module 22 is configured to, at each of the test distances, control the lidar to turn on the shooting mode, collect the detection point cloud data projected by the lidar onto the reflector in different field-of-view regions, and obtain the total number of theoretical points of the lidar falling on the reflector within each field-of-view region; wherein, the overall field of view of the lidar is divided into a plurality of the field-of-view regions, and the field-of-view regions include a central field-of-view region and a plurality of peripheral field-of-view regions.

[0109] The performance calculation module 23 is configured to determine the ranging upper limit value of the lidar for each of the field-of-view regions based on the detection point cloud data and the total number of theoretical points of each of the field-of-view regions at each of the test distances.

[0110] The debugging module 24 is configured to adjust the detection signal strength of the lidar for the field-of-view region to be debugged, so as to reduce the difference between the ranging upper limit value of the lidar for the field-of-view region to be debugged and the ranging upper limit value of the lidar for the central field-of-view region; wherein, the field-of-view region to be debugged is a peripheral field-of-view region where the difference between the ranging upper limit value and the ranging upper limit value corresponding to the central field-of-view region is greater than a set ranging difference threshold.

[0111] The specific working processes of each module can refer to the working process of the lidar debugging device described in the above embodiments, and will not be elaborated here.

[0112] The lidar debugging device may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The lidar debugging device may include, but is not limited to, a processor 31 and a memory 32. Those skilled in the art can understand that the lidar debugging device may further include input / output devices, network access devices, a bus, etc.

[0113] The processor 31 may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor 31 is the control center of the lidar debugging device, and connects various parts of the entire lidar debugging device through various interfaces and lines.

[0114] The memory 32 can be used to store the computer programs and / or modules. By running or executing the computer programs and / or modules stored in the memory 32 and calling the data stored in the memory 32, the processor 31 realizes various functions of the lidar debugging device. The memory 32 mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as an image playback function, etc.); the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory 32 can include high-speed random access memory, and can also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one magnetic disk storage device, flash device, or other volatile solid-state storage devices.

[0115] Among them, if the modules integrated in the lidar debugging device 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 such an understanding, to implement all or part of the processes in the above-mentioned embodiment methods of the present invention, it can also be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor 31, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0116] The embodiment of the present invention also provides a computer program product, including a computer program / instructions. When the computer program / instructions are executed by a processor, the lidar debugging method described in any of the above embodiments is implemented.

[0117] The above is the preferred implementation manner of the present invention. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements are also regarded as the protection scope of the present invention.

Claims

1. A method for lidar debugging, characterized in that, Comprising: Controlling the relative movement of the lidar and the reflector to different test distances; At each of the test distances, controlling the lidar to turn on the shooting mode, collecting the detection point cloud data projected by the lidar onto the reflector in different field-of-view regions, and obtaining the total number of theoretical points that fall on the reflector within each field-of-view region of the lidar; wherein, the overall field of view of the lidar is divided into a plurality of the field-of-view regions, and the field-of-view regions include a central field-of-view region and a plurality of edge field-of-view regions; Determining the ranging upper limit value of the lidar for each of the field-of-view regions based on the detection point cloud data and the total number of theoretical points for each of the field-of-view regions at each of the test distances; Adjusting the detection signal intensity of the lidar for the field-of-view region to be debugged to reduce the difference between the ranging upper limit value of the lidar for the field-of-view region to be debugged and the ranging upper limit value of the lidar for the central field-of-view region; wherein, the field-of-view region to be debugged is an edge field-of-view region where the difference between the ranging upper limit value and the ranging upper limit value corresponding to the central field-of-view region is greater than the set ranging difference threshold.

2. The method for debugging a lidar according to claim 1, wherein The determining the ranging upper limit value of the lidar for each of the field-of-view regions based on the detection point cloud data and the total number of theoretical points for each of the field-of-view regions at each of the test distances includes: Determining the total number of valid points of the lidar for each of the field-of-view regions at each of the test distances based on the detection point cloud data, and calculating the detection success rate of the lidar for each of the field-of-view regions at each of the test distances based on the total number of valid points and the total number of theoretical points; For the first field-of-view region, taking the maximum test distance at which the detection success rate is greater than the preset ratio threshold as the ranging upper limit value of the lidar for the first field-of-view region; wherein, the first field-of-view region is any one of all the field-of-view regions.

3. The method for debugging a lidar according to claim 2, wherein, The detection signal intensity of the lidar for the field-of-view region to be debugged is adjusted by the following method: Generating a fitting formula with the test distance as the independent variable and the detection success rate of the lidar for the central field-of-view region as the dependent variable; Inputting the ranging upper limit value of the lidar for the field-of-view region to be debugged into the fitting formula to obtain the target detection success rate; Based on the corresponding relationship between the detection success rate associated with the detection signal intensity and the ranging upper limit value of the lidar for the field-of-view region to be debugged preset, calculating the target signal intensity according to the target detection success rate; Adjusting the detection signal intensity of the lidar for the field-of-view region to be debugged so that the signal intensity of the lidar for the field-of-view region to be debugged is the target signal intensity.

4. The method for debugging a lidar according to claim 1, wherein The controlling the relative movement of the lidar and the reflector to different test distances includes: Controlling the turntable carrying the reflector to move to the test position to perform the lidar debugging method at the test position.

5. The method for debugging a lidar according to claim 1, wherein Also comprising: Controlling the movement of the reflector to the designated test distance position; At the test distance position, using the lidar to determine the valid points in each of the field-of-view regions at the test distance position and the ranging values of the valid points; Calculate the average ranging value of the ranging values of all the valid points in the first field of view region; wherein, the first field of view region is any one of all the field of view regions; Calculate the ranging accuracy of the first field of view region based on the ranging values of all the valid points and the average ranging value, and calculate the ranging accuracy based on the average ranging value and the actual distance from the lidar to the test distance position; For the first field of view region, perform a quadratic calculation on the difference between the ranging value of each valid point and the actual distance from the lidar to the test distance position, and then perform a summation operation to obtain an intermediate value; calculate the flatness value according to the intermediate value and the number of valid points; wherein, the flatness value has a positive correlation with the intermediate value, and the flatness value has a negative correlation with the number of valid points.

6. The method for debugging a lidar according to claim 1, wherein Further includes: Control the turntable carrying the reflector to move to a specified test distance position; At the test distance position, control the turntable carrying the lidar to rotate at a preset rotation step, and at each rotation angle of the turntable carrying the lidar, control the lidar to turn on the shooting mode to collect the detection point cloud data projected by the lidar onto the reflector at different rotation angles as the field of view angle test point cloud data; Determine the field of view angle value of the lidar based on the field of view angle test point cloud data.

7. A lidar debugging device, characterized in that, Includes: A movement control module for controlling the relative movement of the lidar and the reflector to different test distances; A detection module for, at each test distance, controlling the lidar to turn on the shooting mode, collecting the detection point cloud data projected by the lidar onto the reflector in different field of view regions, and obtaining the total number of theoretical points that the lidar falls on the reflector within each field of view region; wherein, the overall field of view of the lidar is divided into several field of view regions, and the field of view regions include a central field of view region and several peripheral field of view regions; A performance calculation module for determining the ranging upper limit value of the lidar for each field of view region based on the detection point cloud data and the total number of theoretical points of each field of view region at each test distance; A debugging module for adjusting the detection signal strength of the lidar for the field of view region to be debugged to reduce the difference between the ranging upper limit value of the lidar for the field of view region to be debugged and the ranging upper limit value of the lidar for the central field of view region; wherein, the field of view region to be debugged is a peripheral field of view region where the difference between the ranging upper limit value and the ranging upper limit value corresponding to the central field of view region is greater than the set ranging difference threshold.

8. A lidar debugging device, characterized in that, Includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the lidar debugging method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the lidar debugging method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by a processor, the method for debugging a lidar as described in any one of claims 1 to 6 is implemented.

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