A method and device for approximating edge fitting of laser radar point cloud data

Abstract

The present application discloses an approximate laser radar point cloud data edge fitting method, comprising the following steps: when the adjacent first scanning point and second scanning point are respectively the foreground point and the background point, the positions of the first scanning point and the second scanning point are respectively used as the first boundary and the second boundary; scanning is performed again to obtain a new first scanning point and a new second scanning point; when the new first scanning point is between the first boundary and the second boundary, the first boundary is updated with the first scanning point; when the new second scanning point is between the first boundary and the second boundary, the second boundary is updated with the second scanning point; and the position of the foreground edge point is calculated by interpolation based on the positions of the first boundary and the second boundary. The present application also includes a device for implementing the method. The present application solves the problem of large edge errors during laser radar scanning.

Description

Technical Field

[0001] The present application relates to the field of laser radar technology, and in particular to an approximate laser radar point cloud data edge fitting method and device. Background Art

[0002] Object edge detection in 3D point clouds plays a crucial role in applications such as 3D reconstruction, robot navigation and positioning, and LiDAR and visible-light camera calibration. LiDAR-based edge detection can be broadly categorized into two methods: indirect and direct. The indirect method fuses LiDAR and visible-light camera data to identify points visible to the camera but invisible to the LiDAR. This method has the advantage of capturing edges in more locations within the LiDAR point cloud. However, its implementation requires an accurate positional correspondence between the LiDAR and visible-light camera, and visible-light cameras themselves are subject to errors. Direct methods process the raw LiDAR point cloud data directly without the use of other sensors. These methods can, for example, directly obtain the outermost points, determine the object's 3D gradient, or normalize the point cloud to a common plane for geometric analysis. Compared to indirect methods, these methods offer advantages: faster speed and avoid loss of 3D information. However, the processing is complex, making it unsuitable for automation, and the variety of detectable object shapes is limited.

[0003] Due to the scanning range error and the non-fixed horizontal resolution angle of LiDAR, its edge measurement of objects is inaccurate. Therefore, it is necessary to design an effective edge fitting method for LiDAR 3D point clouds. Summary of the Invention

[0004] This application proposes an approximate edge fitting method and device for LiDAR point cloud data. This method utilizes LiDAR's abrupt change characteristics at object edges and its variable horizontal resolution angle to obtain the edge points closest to the object's edge through multi-frame data processing, thus resolving the problem of large edge errors during LiDAR scanning.

[0005] The present application embodiment proposes an approximate laser radar point cloud data edge fitting method, comprising the following steps:

[0006] When the adjacent first scanning point and the second scanning point are respectively the foreground point and the background point, the positions of the first scanning point and the second scanning point are respectively the first boundary and the second boundary;

[0007] Scan again to obtain a new first scanning point and a new second scanning point. When the new first scanning point is between the first boundary and the second boundary, the first boundary is updated with the first scanning point. When the new second scanning point is between the first boundary and the second boundary, the second boundary is updated with the second scanning point.

[0008] The position of the foreground edge point is calculated by interpolation based on the positions of the first boundary and the second boundary.

[0009] Preferably, the method further comprises the following steps:

[0010] Calculate a fitted straight line based on multiple foreground points;

[0011] The edge point is located on the extension line of the fitting straight line.

[0012] Further preferably, when the position of the foreground edge point is calculated by interpolation based on the positions of the first boundary and the second boundary, the position of the first boundary is represented by a first horizontal angle, the position of the second boundary is represented by a second horizontal angle, and the horizontal angle of the foreground edge point is between the first horizontal angle and the second horizontal angle.

[0013] Further preferably, scanning is performed multiple times to iteratively calculate the position of the foreground edge point until the position difference between the first boundary and the second boundary is smaller than a set threshold.

[0014] Further preferably, scanning is performed multiple times to iteratively calculate the position of the foreground edge point until the position change of the foreground edge point is less than a set threshold.

[0015] Further preferably, a fitting straight line is calculated based on a plurality of foreground points, and the position of the edge point on the extension line of the fitting straight line satisfies the horizontal angle of the foreground edge point.

[0016] The present application also provides an approximate laser radar point cloud data edge fitting device for implementing the method described in any embodiment of the present application, the device comprising:

[0017] an identification module, configured to determine a first boundary and a second boundary based on the first scanning point and the second scanning point, and to update the first boundary and the second boundary when scanning again;

[0018] The determination module is used to calculate the position of the foreground edge point by interpolation according to the positions of the first boundary and the second boundary.

[0019] Furthermore, the device further comprises:

[0020] A fitting module, used for determining a fitting straight line based on a plurality of foreground scanning points;

[0021] The determining module is further configured to determine the coordinates of the foreground edge points on the extension line of the fitting straight line according to the horizontal angles of the foreground edge points.

[0022] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any embodiment of the present application.

[0023] The present application also proposes an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any embodiment of the present application when executing the computer program.

[0024] At least one of the above technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects:

[0025] This method reduces the number of sensors and can still accurately detect edge points even with only a LiDAR. This method is highly effective for edge detection at low-speed LiDARs (5Hz), with superior accuracy, stability, and long-range adaptability compared to direct methods. It also significantly outperforms direct methods for edge detection at high-speed LiDARs (20Hz). Its robustness ensures that detected edge points lie exactly on the LiDAR scan line, preventing incorrect edge points from being detected when the scan line deviates from the edge of an object. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0027] Figure 1 This is the edge error analysis diagram of the lidar measurement;

[0028] Figure 2 This is a flow chart of the edge fitting method for approximate lidar point cloud data;

[0029] Figure 3 Extract area maps for the data;

[0030] Figure 4 It is the vertical segmentation map of the lidar data;

[0031] Figure 5 Define images for the foreground and background;

[0032] Figure 6 Define a graph for the LiDAR coordinate system;

[0033] Figure 7 is the approximate edge detection map;

[0034] Figure 8 This is an embodiment of the edge fitting device for approximate laser radar point cloud data of the present application. DETAILED DESCRIPTION

[0035] To make the purpose, technical solutions, and advantages of this application more clear, the technical solutions of this application will be clearly and completely described below in conjunction with the specific embodiments of this application and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0036] Table 1 Symbols used in this paper

[0037]

[0038]

[0039] The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0040] Figure 1 This is a diagram analyzing the edge error of LiDAR measurements.

[0041] First, it is pointed out that without any processing, the laser radar directly detects the error of the object edge. Figure 1 As shown on the left, d is the horizontal distance from the object edge to the radar, h is the vertical distance from the object to the radar, and e is the edge fitting error. From the trigonometric relationship, it is easy to get:

[0042]

[0043] The actual object edge is measured on the left and right sides, so the actual maximum error will be magnified twice, such as Figure 1 As shown on the right, let d be a fixed length of 500mm, h be 3000mm, 6000mm, and 10000mm, and θ be 0.1°, 0.2°, and 0.4° respectively. Substituting the above theoretical error e, we can get the following table:

[0044] Table 2 Specific values ​​of measurement error 2e

[0045] θ(°)\h(mm) 3000 6000 10000 0.1 10.760 21.086 34.990 0.2 21.514 42.166 69.976 0.4 43.002 84.310 139.928

[0046] It can be seen from Table 2 that if the edge points measured by the lidar are directly used as the final object edge points, the error caused by it is large. This method uses approximate edge fitting to solve the above problem. The specific steps are as follows: Figures 2 to 7 .

[0047] To solve the problem of inaccurate edge fitting caused by the LiDAR scanning distance error, we use the straight line fitting method to fit the straight line where the foreground point cloud is located, and then find a point on this fitted line as the edge point.

[0048] To solve the edge fitting problem caused by the horizontal resolution angle of the lidar, we use the horizontal angle step-by-step approximation method to find edge points on the fitted straight line.

[0049] Figure 2 Flowchart of the edge fitting method for approximate lidar point cloud data.

[0050] The present embodiment provides an approximate laser radar point cloud data edge fitting method, including the following steps 21 to 26:

[0051] Step 21: Select an area containing foreground points and background points in the lidar point cloud;

[0052] This area is composed of a bounding box, which is composed of the maximum point (x max ,y max ,z max ) and the minimum point (x min ,y min ,z min ) indicates that a point (x, y, z) belongs to the region when it satisfies the following formula.

[0053] x min <x<x max

[0054] y min <y<y max

[0055] z min <z<z max

[0056] like Figure 3 As shown, the left picture is the top view and the right picture is the main view. The data of subsequent frames are obtained from this selected bounding box area.

[0057] Step 22: Segment a horizontal scan line from the region;

[0058] LiDAR distance measurements have errors, and the error varies from one radar to another. However, the error is generally around 30mm. (If a LiDAR measures a distance of 10,000mm, the actual distance may be between 9,970mm and 10,030mm.) This results in the LiDAR scanning an object not being a true straight line, but rather a wavy line. Due to the scanning distance error, the edge position may deviate from the majority of points, causing the edge point to be off-line with the majority.

[0059] Step 22A: Acquire the first frame of data in the selected area and classify it.

[0060] This selected area contains multiple horizontal scan lines from top to bottom, which need to be processed sequentially. Since the processing flow for each line is the same, we will use the same process for one line as an example, and the rest will follow. Therefore, it is necessary to distinguish these horizontal lines. Each LiDAR scan point has an ID number, and points belonging to the same horizontal scan line have the same ID. This means that from the raw data, each point can be distinguished based on its ID number.

[0061] The first frame data is divided according to the ID of the lidar scan line, so that the point clouds on the same scan line are classified into one category. Figure 4 In order to classify the lidar point cloud according to its classification results, the point clouds of different scan lines have been represented by straight lines of different line types.

[0062] Step 22B: Preferably, the method further comprises the following step: calculating a fitting straight line according to a plurality of foreground points.

[0063] Fit the straight line where the foreground point cloud scan line is located, such as Figure 5 L1 in this step is a key step in the algorithm, and the more robust RANSAC method is used to fit the linear equation.

[0064] The fitted straight line information can be expressed as:

[0065]

[0066] Among them, (x0,y0,z0) is a point on the straight line, is the direction vector of the line. At this time, the point cloud used to fit the line is only the data points of the first frame. As subsequent frames are loaded, the foreground point cloud of subsequent frames will also be merged into the foreground point set S of the first frame data. Line It is used for straight line fitting. That is to say, the effect of straight line fitting will change with the foreground point set S Line The increase in the amount of data makes it more credible.

[0067] Step 23: When the adjacent first scanning point and the second scanning point are respectively the foreground point and the background point, the positions of the first scanning point and the second scanning point are respectively used as the first boundary and the second boundary; and the position of the foreground edge point is calculated by interpolation based on the positions of the first boundary and the second boundary.

[0068] Step 23A, taking the left edge point of one of the scan lines as an example, the right edge point and the edge points of the remaining scan lines are obtained in the same way. Figure 5 As shown in the figure, the foreground point cloud and the background point cloud are distinguished by Euclidean clustering. The boundary points F1 and B1 are obtained from the foreground point cloud and the background point cloud, and the ray where they are located is and Calculate its horizontal angle and The horizontal angle is calculated as follows.

[0069] Further preferably, when the position of the foreground edge point is calculated by interpolation based on the positions of the first boundary and the second boundary, the position of the first boundary is represented by a first horizontal angle, the position of the second boundary is represented by a second horizontal angle, and the horizontal angle of the foreground edge point is between the first horizontal angle and the second horizontal angle.

[0070] Previous attractions Horizontal angle As an example, the calculation method of Same thing. Figure 6 Define the diagram for the LiDAR coordinate system. for:

[0071]

[0072] Step 23B: Further preferably, a fitting line is calculated based on the plurality of foreground points (see step 22B for the method); the edge point is located on an extension line of the fitting line. The position of the edge point on the extension line of the fitting line satisfies the horizontal angle of the foreground edge point.

[0073] Step 23C: Find a point M1 on the fitted line L1 as the edge point of the first frame. The search method is as follows:

[0074] Calculate two boundary points and The median value is the horizontal angle of the edge point.

[0075]

[0076] Find the horizontal angle in the fitted straight line Corresponding points As edge point M1. The solution of edge point M1 is as follows:

[0077] Depend on Solving the following equation, we can get t = t ′

[0078]

[0079] Note that when When it is 90°, we can get and then So the edge point of the first frame for:

[0080]

[0081]

[0082] Step 24: Compare the boundary of the subsequent frame with the initial boundary and perform an approximate search for edge points.

[0083] Step 24A: Scan again to obtain a new first scanning point and a new second scanning point. When the new first scanning point is between the first boundary and the second boundary, the first boundary is updated with the first scanning point; when the new second scanning point is between the first boundary and the second boundary, the second boundary is updated with the second scanning point. Figure 7 is an embodiment.

[0084] Step 24B: interpolate and calculate the position of the foreground edge point based on the updated positions of the first boundary and the second boundary, using the same calculation method as step 23C.

[0085] Step 25: Repeat the subsequent frames until the edge point position does not change significantly or the specified number of running frames is reached.

[0086] Further preferably, scanning is performed multiple times to iteratively calculate the position of the foreground edge point until the position difference between the first boundary and the second boundary is smaller than a set threshold.

[0087] Further preferably, scanning is performed multiple times to iteratively calculate the position of the foreground edge point until the position change of the foreground edge point is less than a set threshold.

[0088] It should be noted that step 23C and step 24B are optional. In another embodiment of the present application, the positions of the edge points can be finally calculated according to the method of step 23C based on the determination of the first boundary and the second boundary in step 25.

[0089] Step 26: Repeat the process for other scan lines to obtain edge points of all scan lines.

[0090] Figure 7 It is an approximate edge detection map.

[0091] Add the foreground point of frame i to the foreground point set S Line , fit a new straight line L i , perform approximation to find the edge point M i The symbols of the relevant scan lines, measurement points and edge points are as follows: Figure 7 shown.

[0092] The measurement point is the most edge point F that can be obtained by direct scanning of the laser radar. i and B i ;

[0093] The meaning of the edge point is the point M closest to the edge detected by the algorithm. i ;

[0094] The ray is the line where the foreground / background measurement point is located when the laser radar is directly scanned.

[0095] The boundary line is the foreground / background ray closest to the edge detected by the algorithm

[0096] exist Figure 7 In ①~④, the triangle is the measurement point, the solid circle point is the edge point to be solved in the current frame, the hollow circle point is the edge point that has been solved in the previous frame, the dot-dash line is the two boundary lines, and the dotted line is the ray where the measurement point is located.

[0097] The measurement points obtained by the first scan line (the ray where the first scan point is located) and the second scan line (the ray where the second scan point is located) are not the edge points we need because they both have theoretical errors. Therefore, we take the intersection of the midline of these two scan lines and the fitting straight line as the edge point, as shown in Formulas 1 and 2.

[0098] like Figure 7 ①, if the background ray of the current frame (the ray where the second scan point is located) and the foreground ray (The ray where the first scanning point is located) is relative to the boundary line Approaching inward, the edge point M of the current frame i Take the median of the horizontal angles of the two rays, and then use the method of finding the point with a known angle in step 23 to find the edge point M. i Update boundary lines for That is, when a subsequent frame of data arrives and it is found that the new first and second scan lines (dashed lines) are approaching the center, the first and second boundary lines are updated to dashed lines. The edge point position is calculated again to be the center line position of the updated first and second boundary lines.

[0099] Figure 7 ② If the background ray of the current frame (the ray where the second scan point is located) and the foreground ray (The ray where the first scanning point is located) is not relative to the boundary line of the previous frame Approaching inward, the edge point M of the current frame i Take the edge point M of the previous frame i-1 , that is, no change. That is to say, when the subsequent frame of data arrives, we find that the new first and second scan lines (dashed lines) are not approaching the center, then no operation is performed, and the edge point obtained by the previous approximation is still used as the edge point obtained by this calculation.

[0100] The following two situations are more special, that is, the situation where only one side is approaching. We need to use the data of the edge point of the previous frame to solve the data of this frame. When the subsequent frame data arrives, we find that among the new first and second scan lines (dashed lines), only the second scan line approaches the center, then update the second boundary line to a dotted line. The edge point at this time is the center position of the updated second boundary line and the ray where the edge point of the previous frame is located. When the subsequent frame data arrives, we find that among the new first and second scan lines (dashed lines), only the first scan line approaches the center, then update the first boundary line to a dotted line. The edge point at this time is the center position of the updated first boundary line and the ray where the edge point of the previous frame is located.

[0101] For example, Figure 7 ③If there is only background ray in the current frame (The ray where the second scanning point is located) relative to the boundary line Approaching inward, the edge point M of the current frame i The horizontal angle of the background ray and the edge point M of the previous frame i-1 The median of the horizontal angle is obtained by using the method of finding the point with a known angle in step 23 to find the edge point M. i .

[0102] Update Boundary Lines for

[0103] For example, Figure 7 ④ If there is only the foreground ray of the current frame (The ray where the first scanning point is located) relative to the boundary line Approaching inward, the edge point M of the current frame i Take foreground ray and the edge point M of the previous frame i-1 The median of the horizontal angle is obtained by using the method of finding the point with a known angle in step 23 to find the edge point M. i Update boundary lines for

[0104] Figure 8 This is an embodiment of the edge fitting device for approximate laser radar point cloud data of the present application.

[0105] The present application also provides an approximate laser radar point cloud data edge fitting device for implementing the method described in any embodiment of the present application, the device comprising:

[0106] The identification module 81 is used to determine the first boundary and the second boundary according to the first scanning point and the second scanning point, and is also used to update the first boundary and the second boundary when scanning again; the details are as described in step 23A and step 24, which will not be repeated here.

[0107] The determination module 82 is configured to interpolate and calculate the position of the foreground edge point based on the positions of the first boundary and the second boundary, as shown in step 23C, formula (1) or (2).

[0108] Furthermore, the device further comprises:

[0109] The fitting module 83 is used to determine a fitting line according to multiple foreground scanning points; specifically, as in steps 22B and 23B.

[0110] The determination module is further configured to determine the coordinates of the foreground edge points on the extension line of the fitted straight line according to the horizontal angles of the foreground edge points. See step 23C, formula (2) for details.

[0111] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0112] Therefore, the present application also proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in any embodiment of the present application.

[0113] Furthermore, the present application also proposes an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in any embodiment of the present application when executing the computer program.

[0114] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0115] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0116] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0117] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0118] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0119] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0120] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0121] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. An approximate laser radar point cloud data edge fitting method, characterized in that: The following steps are involved: When the adjacent first scanning point and the second scanning point are respectively the foreground point and the background point, the positions of the first scanning point and the second scanning point are respectively the first boundary and the second boundary; Scan again to obtain a new first scanning point and a new second scanning point. When the new first scanning point is between the first boundary and the second boundary, the first boundary is updated with the first scanning point. When the new second scanning point is between the first boundary and the second boundary, the second boundary is updated with the second scanning point. Calculating a fitting straight line based on a plurality of foreground points; wherein the edge points are located on an extension line of the fitting straight line; The position of the foreground edge point is calculated by interpolation based on the positions of the first boundary and the second boundary.

2. The edge fitting method for approximate laser radar point cloud data according to claim 1, characterized in that: When the position of the foreground edge point is calculated by interpolation based on the positions of the first boundary and the second boundary, the position of the first boundary is represented by a first horizontal angle, the position of the second boundary is represented by a second horizontal angle, and the horizontal angle of the foreground edge point is between the first horizontal angle and the second horizontal angle.

3. The edge fitting method for approximate laser radar point cloud data according to claim 1, characterized in that: The scanning is performed multiple times, and the positions of the foreground edge points are iteratively calculated until the position difference between the first boundary and the second boundary is less than a set threshold.

4. The approximate laser radar point cloud data edge fitting method according to claim 1, wherein: The scanning is performed multiple times, and the position of the foreground edge point is iteratively calculated until the position change of the foreground edge point is less than a set threshold.

5. The approximate laser radar point cloud data edge fitting method according to claim 3, characterized in that: A fitting straight line is calculated based on a plurality of foreground points, and a position of the edge point on an extension line of the fitting straight line satisfies a horizontal angle of the foreground edge point.

6. An approximate laser radar point cloud data edge fitting device, used to implement the method according to any one of claims 1 to 5, characterized in that: include: an identification module, configured to determine a first boundary and a second boundary based on the first scanning point and the second scanning point, and to update the first boundary and the second boundary when scanning again; The determination module is used to calculate the position of the foreground edge point by interpolation according to the positions of the first boundary and the second boundary.

7. The device for edge fitting of approximate laser radar point cloud data according to claim 6, wherein: Also includes: A fitting module, used for determining a fitting straight line based on a plurality of foreground scanning points; The determining module is further configured to determine the coordinates of the foreground edge points on the extension line of the fitting straight line according to the horizontal angles of the foreground edge points.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 5 is implemented.

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