A laser radar beam parameter detection method, device, equipment and medium

Abstract

The present invention relates to a laser radar beam parameter detection method, device, equipment and medium. The method obtains a point cloud set of a frame sampled by the laser radar, determines the position information of each sampling point according to the point cloud set, determines the elevation angle set and / or azimuth angle set of the laser radar beam according to the position information of each sampling point, clusters the elevation angle set and / or the azimuth angle set to obtain a segmentation set, and obtains the laser radar beam parameters according to the segmentation set. Compared with the prior art, the present invention enables the staff to obtain the laser radar beam parameters even when the description document is missing, the radar model is unclear, etc., and then carry out related repair, design and other work, and has a good application prospect.

Description

Technical Field

[0001] The present invention relates to the field of laser radar technology, and in particular to a laser radar beam parameter detection method, device, equipment and medium. Background Art

[0002] LiDAR is a radar system that emits laser beams to detect the position, speed and other characteristic quantities of a target. Its working principle is to transmit a detection signal to the target, and then compare the received signal reflected from the target with the transmitted signal. After appropriate processing, relevant information about the target can be obtained, such as target distance, direction, height, speed, attitude, and even shape parameters. LiDAR can provide robust environmental perception and positioning information for autonomous vehicles or robots. Therefore, with the continuous development of autonomous driving and robotics technology, the application of LiDAR is becoming more and more extensive and in-depth.

[0003] The beams of commonly used mechanical or solid-state laser radars are in a regular array shape, and the array shape is determined by beam parameters such as vertical resolution (number of vertical beams), vertical field of view, horizontal resolution, and horizontal field of view. In actual applications, the correctness of these parameters directly affects the performance of the perception or positioning algorithm.

[0004] Usually, the above parameters can be obtained through the instruction documents attached to the laser radar, the website platform of the laser radar manufacturer, etc. However, in actual application scenarios, special factors such as document loss or unclear model often occur, resulting in the situation that the radar parameters cannot be known. In addition, when the laser radar is used, there will also be scenarios where the wiring harness parameters need to be detected to diagnose whether the laser radar is faulty. Therefore, it is very necessary to invent a method for detecting the wiring harness parameters of the laser radar. Summary of the invention

[0005] In view of this, it is necessary to provide a laser radar beam parameter detection method, device, equipment and medium to solve the problem of how to detect the laser radar beam parameters.

[0006] In order to achieve the above technical objectives, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a laser radar beam parameter detection method, comprising:

[0008] Obtain a point cloud set of a frame sampled by the laser radar, and determine the position information of each sampling point according to the point cloud set;

[0009] Determine the elevation angle set and / or azimuth angle set of the laser radar beam according to the position information of each sampling point;

[0010] Performing clustering processing on the elevation angle set and / or the azimuth angle set to obtain a segmentation set;

[0011] The beam parameters of the laser radar are obtained according to the segmentation set.

[0012] Furthermore, determining the position information of each sampling point according to the point cloud set includes: acquiring three-dimensional coordinate information of each sampling point corresponding to the point cloud set.

[0013] Furthermore, the elevation angle set and / or azimuth angle set of the laser radar beam is determined according to the position information of each sampling point, including: determining the elevation angle and / or azimuth angle of the laser radar beam corresponding to each sampling point according to the three-dimensional coordinate information of each sampling point corresponding to the point cloud set, and forming an elevation angle set and / or an azimuth angle set.

[0014] Further, clustering the elevation angle set and / or the azimuth angle set to obtain a segmentation set includes:

[0015] The elevation angle set or the azimuth angle set is used as a to-be-processed set, and a certain angle value in the to-be-processed set is selected as a temporary reference value;

[0016] First clustering: clustering the angle values ​​in the to-be-processed set based on the temporary reference value, obtaining angle values ​​that meet the set conditions and obtaining a temporary set;

[0017] Second clustering: taking the average of all angle values ​​in the temporary set as an intermediate reference value, clustering the angle values ​​in the difference set between the to-be-processed set and the temporary set based on the intermediate reference value, obtaining angle values ​​that meet the set conditions and merging them into the temporary set;

[0018] The third clustering: repeatedly performing the second clustering until the number of angle values ​​in the temporary set no longer increases, and obtaining an intermediate set;

[0019] Selecting an angle value that is not in the intermediate set from the set to be processed as a temporary reference value, and repeatedly performing the first clustering, the second clustering, and the third clustering in sequence until the set to be processed is an empty set, thereby obtaining a plurality of the intermediate sets;

[0020] A plurality of segmentation sets are obtained based on the plurality of intermediate sets.

[0021] Furthermore, the angle values ​​in the set to be processed are clustered based on the temporary baseline value to obtain angle values ​​that meet the set conditions and obtain a temporary set, including: obtaining a set number of angle values ​​in the set to be processed with the smallest difference from the temporary baseline value, and selecting angle values ​​whose difference with the temporary baseline value is less than a first set threshold from the obtained set number of angle values ​​as the temporary set.

[0022] Furthermore, obtaining the plurality of segmentation sets based on the plurality of intermediate sets includes: obtaining the plurality of intermediate sets in which the number of angle values ​​is greater than or equal to a second set threshold value, and taking each of the intermediate sets as a segmentation set.

[0023] Furthermore, obtaining the beam parameters of the laser radar according to the segmentation set includes:

[0024] According to the number of the segmentation sets, the number of laser radar beams is obtained;

[0025] The field of view angle and resolution of the laser radar are obtained according to the difference between the average values ​​of the angle values ​​in the several segmentation sets.

[0026] In a second aspect, the present invention further provides a laser radar beam parameter detection device, comprising:

[0027] An acquisition module is used to obtain a point cloud set of a frame sampled by the laser radar, and determine the position information of each sampling point according to the point cloud set;

[0028] A position analysis module, which determines an elevation angle set and / or an azimuth angle set of the laser radar beam according to the position information of each sampling point;

[0029] A clustering segmentation module, used for performing clustering processing on the elevation angle set and / or the azimuth angle set to obtain a segmentation set;

[0030] An output module is used to obtain beam parameters of the laser radar according to the segmentation set.

[0031] In a third aspect, the present invention further provides an electronic device, including a memory and a processor, wherein:

[0032] Memory, used to store programs;

[0033] The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the laser radar beam parameter detection method in any of the above implementations.

[0034] In a fourth aspect, the present invention also provides a computer-readable storage medium for storing computer-readable programs or instructions. When the program or instructions are executed by a processor, the steps in the laser radar beam parameter detection method in any of the above-mentioned implementation methods can be implemented.

[0035] The present invention provides a laser radar beam parameter detection method, device, equipment and medium. By acquiring a point cloud set of a frame sampled by the laser radar, and then obtaining the elevation angle set and / or azimuth angle set of each transmitting beam of the laser radar according to the position information in the point cloud set, the elevation angle or azimuth angle set is clustered, and the required beam parameters can be obtained through the segmented set obtained after clustering. In this way, the staff can still obtain the beam parameters of the laser radar even when the instruction document is missing, the radar model is unclear, etc., and then carry out related repair, design and other work, which has a good application prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A method flow chart of an embodiment of a laser radar beam parameter detection method provided by the present invention;

[0037] Figure 2 for Figure 1 A method flow chart of an embodiment of step S103;

[0038] Figure 3 A schematic structural diagram of an embodiment of a laser radar beam parameter detection device provided by the present invention;

[0039] Figure 4 A schematic structural diagram of an embodiment of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0040] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0041] First of all, the specific meanings of some relevant terms used in this article are as follows:

[0042] One frame of laser radar: When the laser radar is in operation, its detection beam can be regarded as scanning in one direction, and the data obtained by the laser radar in one cycle of polling along the scanning direction can be regarded as one frame of data. For example, if the multiple beams in the laser radar are arranged in the same vertical plane, it rotates back and forth along a vertical axis and scans when working, and its horizontal detection angle is 140°, that is, the laser emitting device inside it can rotate 140° in the horizontal plane, then all the data that can be obtained by the laser radar rotating 140° is one frame of data.

[0043] Point cloud collection: Each beam of the laser radar is emitted and irradiated onto a detection point, which is a sampling point. The beam is reflected and received by the laser radar to obtain data. The data of the sampling point generally includes the coordinates of the detection point relative to the laser radar coordinate system, color information, reflection intensity information, echo number information and other data. The collection of data from multiple sampling points is a point cloud collection.

[0044] Elevation Angle: The angle between the detection beam in the lidar and the plane in which the lidar rotates.

[0045] Azimuth: The angle that the detection beam in the lidar sweeps along its scanning direction starting from a specified reference.

[0046] LiDAR beam parameters: including the number of vertical beams, vertical resolution, vertical field of view, number of horizontal beams, horizontal resolution and horizontal field of view of the LiDAR, etc., which are determined according to specific needs in practice.

[0047] In the description of the present application, “plurality” means two or more than two, unless otherwise clearly and specifically defined.

[0048] The present invention provides a laser radar beam parameter detection method, device, equipment and storage medium, which are described below respectively.

[0049] A specific embodiment of the present invention discloses a laser radar beam parameter detection method. When implemented, Figure 1 As shown, the laser radar beam parameter detection method includes:

[0050] S101, obtaining a point cloud set of a frame sampled by a laser radar, and determining the position information of each sampling point therein according to the point cloud set;

[0051] S102, determining an elevation angle set and / or an azimuth angle set of a laser radar beam according to the position information of each sampling point;

[0052] S103, performing clustering processing on the elevation angle set and / or the azimuth angle set to obtain a segmentation set;

[0053] S104. Obtain beam parameters of the laser radar according to the segmentation set.

[0054] The present embodiment provides a laser radar beam parameter detection method, which first obtains a point cloud set of a frame sampled by the laser radar, and then obtains the elevation angle set and / or azimuth angle set of each transmitting beam of the laser radar according to the position information in the point cloud set, and clusters the elevation angle or azimuth angle sets, and the required beam parameters can be obtained through the segmented set obtained after clustering. In this way, the staff can still obtain the beam parameters of the laser radar even when the instruction document is missing or the radar model is unclear, and then carry out related repair, design and other work, which has a good application prospect.

[0055] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0056] As a preferred embodiment, in step S101 of this embodiment, the position information of each sampling point therein is determined according to the point cloud set, including: obtaining the three-dimensional coordinate information of each sampling point in the point cloud set. Each sampling point in the point cloud set includes a lot of data, including position information representing the position of the sampling point, which is generally the coordinate of the detection point relative to the laser radar coordinate system. The laser radar coordinate system is generally calibrated by the manufacturer during production, and the coordinates in the data obtained by its detection are the coordinates relative to the coordinate system. Depending on the type of coordinate system, the above coordinates can be three-dimensional coordinates, polar coordinates, etc. The position information obtained in this embodiment is three-dimensional coordinate information, and the three-dimensional coordinate information can facilitate the calculation of elevation angles and azimuth angles in subsequent steps.

[0057] The above process can be implemented by a written computer program, or by directly observing the detected data manually, and recording the three-dimensional coordinate information in the data. Specifically, as an example, the three-dimensional coordinates detected in this embodiment are:

[0058] A three-dimensional Cartesian coordinate system is established with the laser radar's beam emission point as the origin. The beam emission point is the emission point of the laser transmitter in the laser radar, and multiple beams are emitted and diffused from this emission point. At the same time, this point is also located on the rotation axis of the laser transmitter. In the three-dimensional Cartesian coordinate system, the rotation axis of the laser radar for scanning motion is the z-axis, and the plane where the laser transmitter rotates is parallel to the xoy plane. The specific direction of the x-axis can be set arbitrarily in theory. For the convenience of calculation and understanding, the positive direction of the x-axis in this embodiment is directly in front of the laser radar in the initial state, and the x-axis, y-axis and z-axis conform to the right-hand rule. In this way, the three-dimensional coordinate information set of each sampling point can be obtained through the point cloud set: L = {p 0 ,p 1 ...p N}, where L represents the three-dimensional coordinate information set of each sampling point, and N is an arbitrary positive integer, indicating that there are N+1 elements in the set, which can be obtained by p n Represents any element in the set, whose subscript n is any integer in the range [0,N], p n The three-dimensional coordinate information contained in the element is [x n ,y n ,z n ], where x n ,y n , z n They are p n The detection point represented by the sampling point corresponding to the element is located at the coordinates on the x-axis, y-axis and z-axis in the above three-dimensional Cartesian coordinate system.

[0059] Furthermore, in S102 of this embodiment, the elevation angle set and / or azimuth angle set of the laser radar beam is determined according to the position information of each sampling point, specifically including: determining the elevation angle and / or azimuth angle of the laser radar beam corresponding to each sampling point according to the three-dimensional coordinate information of each sampling point in the point cloud set, and forming an elevation angle set and / or an azimuth angle set.

[0060] Specifically, based on the above-mentioned laser radar coordinate system and the obtained three-dimensional coordinate information, in this embodiment:

[0061] By formula Get the elevation angle of the sampling point, where β n That is p n The elevation angle of the laser beam corresponding to the sampling point represented by the element, x n ,y n , z n They are p n The detection point represented by the sampling point corresponding to the element is located at the coordinates of the x-axis, y-axis and z-axis in the above three-dimensional Cartesian coordinate system;

[0062] By formula Get the azimuth of the sampling point, where λ n That is p n The azimuth of the laser beam corresponding to the sampling point represented by the element, x n ,y n , z n They are p n The detection point represented by the sampling point corresponding to the element is located at the coordinates on the x-axis, y-axis and z-axis in the above three-dimensional Cartesian coordinate system.

[0063] It is understandable that when the coordinate system used by the laser radar is different, the calculation method may also be different. For example, when the laser radar uses a polar coordinate system, the elevation angle and azimuth angle can be directly read from the coordinates of the sampling point without calculation. After calculating each element in the above three-dimensional coordinate information, all the elevation angles obtained are the elevation angle set, and all the azimuth angles are the azimuth angle set. In practice, depending on the specific beam parameters you want to obtain, you can only obtain the elevation angle set or the azimuth angle set, or you can obtain both.

[0064] After obtaining the elevation angle set or the azimuth angle set, it is necessary to perform clustering processing on the angle values ​​in the above set, that is, to execute step S103. The clustering processing in step S103 can adopt any clustering method such as Euclidean clustering. In this embodiment, a more preferred clustering processing method is provided. The clustering processing is as follows: Figure 2 As shown, including:

[0065] S201, taking the elevation angle set or the azimuth angle set as a to-be-processed set, and selecting a certain angle value in the to-be-processed set as a temporary reference value;

[0066] S202, first clustering: clustering the angle values ​​in the to-be-processed set based on the temporary reference value, obtaining angle values ​​that meet the set conditions and obtaining a temporary set;

[0067] S203, second clustering: taking the average of all angle values ​​in the temporary set as an intermediate reference value, and clustering the angle values ​​in the difference set between the to-be-processed set and the temporary set based on the intermediate reference value, obtaining angle values ​​that meet the set conditions and merging them into the temporary set;

[0068] S204, third clustering: repeatedly performing the second clustering until the number of angle values ​​in the temporary set no longer increases, and an intermediate set is obtained;

[0069] S205, selecting an angle value that is not in the intermediate set from the set to be processed as a temporary reference value, and repeatedly performing the first clustering, the second clustering, and the third clustering in sequence until the set to be processed is an empty set, thereby obtaining a plurality of the intermediate sets;

[0070] S206: Obtain a plurality of the segmentation sets based on the plurality of the intermediate sets.

[0071] The process of dividing a set of physical or abstract objects into multiple classes consisting of similar objects is called clustering. The cluster generated by clustering is a set of data objects that are similar to objects in the same cluster and different from objects in other clusters. In this embodiment, the processed elevation set and azimuth set are clustered to obtain multiple segmentation sets. The sampling points mapped by the angle values ​​in each segmentation set can be regarded as sampling points with similar features, such as the set of sampling points detected by the same detection beam at all times in a frame, or the set of all sampling points collected by all laser beams at a certain time in a frame. The required beam parameters can be obtained based on these segmentation sets.

[0072] Specifically, in the above step S202, the angle values ​​in the to-be-processed set are clustered based on the temporary benchmark value, and the angle values ​​that meet the set conditions are obtained to obtain a temporary set, including: obtaining a set number of angle values ​​in the to-be-processed set with the smallest difference from the temporary benchmark value, and selecting the angle value whose difference with the temporary benchmark value is less than a first set threshold from the obtained set number of angle values ​​as the temporary set.

[0073] The set number of angle values ​​with the smallest difference from the temporary benchmark value is the set number of angle values ​​in the set to be processed, with the difference from the temporary benchmark value from small to large, which can be obtained by a simple difference, sorting and screening method, or by an existing algorithm such as an exhaustive proximity search algorithm. The set number can ensure that the number of angle values ​​clustered into the temporary set at one time will not be too many, that is, at most the set number, so that after the subsequent calculation of the average value, the change of the temporary benchmark value is small, and there will be no sudden change with a large difference, ensuring that the angle values ​​clustered into the temporary set each time are the closest angle values, thereby improving the clustering accuracy.

[0074] The first threshold is set as a condition for filtering data, which makes the angle values ​​with a small difference from the temporary benchmark value and similar features be clustered in a temporary set. Like the set number, it can be flexibly set according to specific circumstances.

[0075] Similarly, in step S203, this embodiment also uses the same set number and the first set threshold as in the first clustering for clustering. In practice, other set conditions can also be replaced to complete clustering. It is worth noting that when performing the second clustering, the average of all angle values ​​in the temporary set is used as the reference value for the next clustering screening. The average can be regarded as a common feature of the sampling points mapped by all angle values ​​in the temporary set, so that the features of the angle values ​​clustered together each time are closest, the clustering effect is more accurate, and it can effectively eliminate noise and reduce the error of the clustering result, which greatly improves the detection accuracy of the laser radar beam parameter detection method.

[0076] After the first clustering and the second clustering, although a temporary set with similar angle values ​​is established, there may still be angle values ​​in the set to be processed that have not been clustered into the temporary set. At this time, step S204 needs to be performed. When the number of angle values ​​in the temporary set no longer increases, it can be considered that all the angle values ​​closest to the initially selected temporary benchmark value are clustered into the temporary set.

[0077] After executing step S205, all angle values ​​in the set to be processed will be traversed and divided into multiple intermediate sets. However, due to factors such as the selection of the initial temporary benchmark value, the accuracy of calculating the average value during clustering, and the distortion when the lidar collects data, there may be errors in the process of dividing into multiple intermediate sets. Some angle values ​​may not be accurately clustered in a certain intermediate set. At this time, step S206 is required to exclude these deviated intermediate sets.

[0078] Specifically, in step S206 of the present embodiment, the obtaining of the plurality of segmentation sets based on the plurality of intermediate sets includes: obtaining the plurality of intermediate sets whose number of angle values ​​is greater than or equal to the second set threshold value, and taking each of them as a segmentation set. The intermediate sets whose number of angle values ​​is less than the second set threshold value in the plurality of intermediate sets are regarded as outliers with errors, and are proposed. The remaining intermediate sets can be used as segmentation sets obtained after the set to be processed is segmented. The second set threshold value can also be flexibly set according to the specific situation.

[0079] For easier understanding, here is another way to explain the above steps:

[0080] Step 1: Assume that a one-dimensional set is A = [a 0 ,a 1 ...a N ], where A is the above-mentioned set to be processed, the elements of which can use the data in the elevation angle set or the data in the direction angle set, and N is an arbitrary positive integer, indicating that there are N+1 elements in the set, which can be an represents any element in the set, that is, the angle value, and its subscript n is any integer in the range [0, N]. n The value of the element is used as a temporary reference value.

[0081] Step 2: Use the exhaustive nearest neighbor search algorithm to find the optimal solution in A-(Q 0 ∪Q 1 ...∪Q m-1 ) to find the set number k and a n The element with the smallest element difference, and select the element with the smallest element difference and a among these k elements n Elements whose element difference is less than the first set threshold r are clustered into a set Q m , and the set Q m As a temporary set. The subscript m is a non-negative integer, indicating that m different a have been replaced before this clustering. n The element is used as a temporary benchmark value, and m intermediate sets have been obtained, namely Q 0 , Q 1 , Q 2 …Q m-1 .

[0082] Step 3: Find Q at this time m The average of all values ​​in A-(Q 0 ∪Q 1 ...∪Q m ) to find the set number k and a n Elements whose element difference is less than the first set threshold r are clustered into the set Q m middle.

[0083] Step 4: Repeat step 3 until Q m The number of elements in Q no longer increases. m It can be regarded as a new intermediate set.

[0084] Step 5: Now add 1 to the value of m, and then 0 ∪Q 1 ...∪Q m ) continues to select any element a n , as the new temporary reference value, and then repeat steps 2, 3 and 4 in sequence until A-(Q 0 ∪Q 1 ...∪Q m ) is an empty set, and finally m intermediate sets are obtained.

[0085] Step 6, delete Q 0 , Q 1 , Q2 …Q m-1 , Q m The sets whose number of elements is less than the second set threshold are selected and the angle values ​​in these sets are marked as outliers, and finally M segmentation sets are obtained.

[0086] After obtaining multiple segmentation sets, the beam parameters to be obtained can be determined according to the characteristics of the segmentation sets. That is, in S104 of this embodiment, the beam parameters of the laser radar are obtained according to the segmentation sets, including:

[0087] The number of laser radar beams is obtained according to the number of the segmentation sets.

[0088] The field of view angle and resolution of the laser radar are obtained according to the difference between the average values ​​of the angle values ​​in the several segmentation sets.

[0089] Specifically, when the elevation angle set is used as the set to be processed in the above step S201, the number of segmented sets obtained can be regarded as the number of beams arranged longitudinally by the laser radar, the difference between the average values ​​of the angle values ​​in each segmented set is the angle between the two beams, the maximum value of the difference in the average values ​​is the vertical field of view of the laser radar, and the minimum value of the difference in the average values ​​can be regarded as the vertical resolution of the laser radar. Similarly, when the elevation angle set is used as the set to be processed in the above step S201, the number of segmented sets obtained can be regarded as the sampling frequency of the laser radar in one cycle of horizontal scanning, the difference between the average values ​​of the angle values ​​in each segmented set is the angle between two adjacent sampling moments, the maximum value of the difference in the average values ​​is the horizontal field of view of the laser radar, and the minimum value of the difference in the average values ​​can be regarded as the horizontal resolution of the laser radar. In addition, the uniformity of the laser radar beam arrangement and other information related to the beam parameters can also be judged by the difference, and the specific judgment method can be determined according to the actual situation.

[0090] In order to better implement the path planning method in the embodiment of the present invention, based on the path planning method, correspondingly, please refer to Figure 3 , Figure 3 This is a schematic diagram of the structure of an embodiment of a laser radar beam parameter detection device provided by the present invention. The embodiment of the present invention provides a laser radar beam parameter detection device 300, including:

[0091] The acquisition module 301 is used to obtain a point cloud set of a frame sampled by the laser radar, and determine the position information of each sampling point therein according to the point cloud set;

[0092] A position analysis module 302, used to determine the elevation angle set and / or azimuth angle set of the laser radar beam according to the position information of each sampling point;

[0093] A clustering segmentation module 303, configured to perform clustering processing on the elevation angle set and / or the azimuth angle set to obtain a segmentation set;

[0094] The output module 304 is used to obtain the beam parameters of the laser radar according to the segmentation set.

[0095] It should be noted here that the corresponding device 300 provided in the above embodiment can implement the technical solutions described in the above method embodiments. The specific implementation principles of the above modules or units can refer to the corresponding contents in the above method embodiments, which will not be repeated here.

[0096] See also Figure 4 , Figure 4 The schematic diagram of the structure of the electronic device 400 provided in the embodiment of the present invention. Based on the above laser radar beam parameter detection method, the present invention also provides an electronic device 400, which can be a computing device such as a mobile terminal, a desktop computer, a notebook, a palm computer and a server. The electronic device 400 includes a processor 401, a memory 402 and a display 403. Figure 4 Only some components of the electronic device 400 are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0097] In some embodiments, the memory 402 may be an internal storage unit, such as a hard disk or a memory. In other embodiments, the memory 402 may also be an external storage device, such as a plug-in hard disk equipped on a path planning device, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Further, the memory 402 may also include both an internal storage unit and an external storage device. The memory 402 is used to store application software and various types of data installed in the electronic device 400, such as program codes for realizing laser radar beam parameter detection. The memory 402 can also be used to temporarily store data that has been output or is to be output. In one embodiment, a laser radar beam parameter detection program is stored on the memory 402, and the laser radar beam parameter detection program can be executed by the processor 401, thereby realizing the laser radar beam parameter detection method of each embodiment of the present application.

[0098] In some embodiments, the processor 401 may be a central processing unit (CPU), a microprocessor or other data processing chip, used to run program codes or process data stored in the memory 402, such as executing a laser radar beam parameter detection method.

[0099] In some embodiments, the display 403 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 403 is used to display information on the electronic device 400 and to display a visual user interface. The components of the electronic device 400 communicate with each other via a system bus.

[0100] In one embodiment, when the processor 401 executes the laser radar beam parameter detection program in the memory 402, the steps in the above laser radar beam parameter detection method are implemented.

[0101] This embodiment also provides a computer-readable storage medium, on which a program readable by a computer is stored. When the program is executed by a processor, the methods and steps provided in the above embodiments can be implemented.

[0102] In summary, the present invention provides a laser radar beam parameter detection method, device, equipment and medium, which first obtains a point cloud set of a frame sampled by the laser radar, and then obtains the elevation angle set and / or azimuth angle set of each transmitting beam of the laser radar according to the position information in the point cloud set, and clusters the elevation angle or azimuth angle sets, and the required beam parameters can be obtained through the segmented set obtained after clustering. In this way, the staff can still obtain the beam parameters of the laser radar even when the instruction document is missing, the radar model is unclear, etc., and then carry out related repair, design and other work, which has a good application prospect.

[0103] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A laser radar beam parameter detection method, characterized in that: include: Obtain a point cloud set of a frame sampled by the laser radar, and determine the position information of each sampling point according to the point cloud set; Determine the elevation angle set and / or azimuth angle set of the laser radar beam according to the position information of each sampling point; Performing clustering processing on the elevation angle set and / or the azimuth angle set to obtain a segmentation set; Obtaining beam parameters of the laser radar according to the segmentation set; The clustering process is performed on the elevation angle set and / or the azimuth angle set to obtain a segmentation set, comprising: The elevation angle set or the azimuth angle set is used as a to-be-processed set, and a certain angle value in the to-be-processed set is selected as a temporary reference value; First clustering: clustering the angle values ​​in the to-be-processed set based on the temporary reference value, obtaining angle values ​​that meet the set conditions and obtaining a temporary set; Second clustering: taking the average of all angle values ​​in the temporary set as an intermediate reference value, clustering the angle values ​​in the difference set between the to-be-processed set and the temporary set based on the intermediate reference value, obtaining angle values ​​that meet the set conditions and merging them into the temporary set; The third clustering: repeatedly performing the second clustering until the number of angle values ​​in the temporary set no longer increases, and obtaining an intermediate set; Selecting an angle value that is not in the intermediate set from the set to be processed as a temporary reference value, and repeatedly performing the first clustering, the second clustering, and the third clustering in sequence until the set to be processed is an empty set, thereby obtaining a plurality of the intermediate sets; Obtaining a plurality of the segmentation sets based on the plurality of the intermediate sets; The clustering of the angle values ​​in the to-be-processed set based on the temporary reference value, obtaining angle values ​​that meet the set conditions and obtaining a temporary set, comprises: Acquire a set number of angle values ​​in the to-be-processed set whose difference with the temporary reference value is the smallest, and select angle values ​​whose difference with the temporary reference value is less than a first set threshold from the acquired set number of angle values ​​as a temporary set; The obtaining of a plurality of segmentation sets based on the plurality of intermediate sets comprises: A plurality of the intermediate sets in which the number of angle values ​​is greater than or equal to a second set threshold are obtained, and each of them is used as a segmentation set.

2. The laser radar beam parameter detection method according to claim 1, characterized in that: Determining the position information of each sampling point according to the point cloud set includes: Obtain the three-dimensional coordinate information of each sampling point corresponding to the point cloud set.

3. The laser radar beam parameter detection method according to claim 2, characterized in that: Determining the elevation angle set and / or azimuth angle set of the laser radar beam according to the position information of each sampling point includes: The elevation angle and / or azimuth angle of the laser radar beam corresponding to each sampling point is determined according to the three-dimensional coordinate information of each sampling point corresponding to the point cloud set, and an elevation angle set and / or an azimuth angle set are formed.

4. The laser radar beam parameter detection method according to claim 1, characterized in that: The step of obtaining the beam parameters of the laser radar according to the segmentation set includes: According to the number of the segmentation sets, the number of laser radar beams is obtained; The field of view angle and resolution of the laser radar are obtained according to the difference between the average values ​​of the angle values ​​in the several segmentation sets.

5. A laser radar beam parameter detection device, characterized in that: include: An acquisition module is used to obtain a point cloud set of a frame sampled by the laser radar, and determine the position information of each sampling point according to the point cloud set; A position analysis module, used to determine the elevation angle set and / or azimuth angle set of the laser radar beam according to the position information of each sampling point; A clustering segmentation module, used for performing clustering processing on the elevation angle set and / or the azimuth angle set to obtain a segmentation set; An output module, used for obtaining beam parameters of the laser radar according to the segmentation set; The clustering process is performed on the elevation angle set and / or the azimuth angle set to obtain a segmentation set, comprising: The elevation angle set or the azimuth angle set is used as a to-be-processed set, and a certain angle value in the to-be-processed set is selected as a temporary reference value; First clustering: clustering the angle values ​​in the to-be-processed set based on the temporary reference value, obtaining angle values ​​that meet the set conditions and obtaining a temporary set; Second clustering: taking the average of all angle values ​​in the temporary set as an intermediate reference value, clustering the angle values ​​in the difference set between the to-be-processed set and the temporary set based on the intermediate reference value, obtaining angle values ​​that meet the set conditions and merging them into the temporary set; The third clustering: repeatedly performing the second clustering until the number of angle values ​​in the temporary set no longer increases, and obtaining an intermediate set; Selecting an angle value that is not in the intermediate set from the set to be processed as a temporary reference value, and repeatedly performing the first clustering, the second clustering, and the third clustering in sequence until the set to be processed is an empty set, thereby obtaining a plurality of the intermediate sets; Obtaining a plurality of the segmentation sets based on the plurality of the intermediate sets; The clustering of the angle values ​​in the to-be-processed set based on the temporary reference value, obtaining angle values ​​that meet the set conditions and obtaining a temporary set, comprises: Acquire a set number of angle values ​​in the to-be-processed set whose difference with the temporary reference value is the smallest, and select angle values ​​whose difference with the temporary reference value is less than a first set threshold from the acquired set number of angle values ​​as a temporary set; The obtaining of a plurality of segmentation sets based on the plurality of intermediate sets comprises: A plurality of the intermediate sets in which the number of angle values ​​is greater than or equal to a second set threshold are obtained, and each of them is used as a segmentation set.

6. An electronic device, characterized in that: comprising a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the laser radar beam parameter detection method described in any one of claims 1 to 4 above.

7. A computer-readable storage medium, characterized in that: Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps in the laser radar beam parameter detection method described in any one of claims 1 to 4 above.

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