Laser system control method, device, electronic device and readable storage medium

Abstract

The present application provides a control method, device, electronic device and readable storage medium for a laser system. The method includes: obtaining a point cloud map of a target area; setting a simulated radar point in the point cloud map according to the walking track and installation information of a real radar; for each simulated radar point, performing a simulated radar scan on the simulated radar point to obtain a simulated single-frame point cloud of the simulated radar point; after segmenting and feature classifying each single-frame point cloud, identifying a positioning laser line according to the segmentation result and classification result of each single-frame point cloud, obtaining positioning laser line information, and the positioning laser line information is used to adjust the number of laser emissions of the real radar, and can add positioning line attributes to the map, so that the real radar can know in advance the emission laser lines that have little impact on positioning, so as to adjust the number of laser emissions of the real radar, thereby solving the unnecessary energy consumption in the positioning and mapping process and increasing the efficiency of positioning.

Description

Technical Field

[0001] The present application belongs to the field of laser technology, and in particular, relates to a control method, device, electronic device and readable storage medium of a laser system. Background Art

[0002] At present, simultaneous positioning and map creation are the key and basis for solving various problems such as exploration, reconnaissance or navigation of mobile robots in unknown environments, and the laser slam system came into being.

[0003] The working process of the laser SLAM system is that the robot starts from an unknown location in an unknown environment, locates its own position and posture through repeatedly observed environmental features during movement, and then builds an incremental map of the surrounding environment based on its own position, thereby achieving the purpose of simultaneous positioning and map construction.

[0004] Among them, the laser slam system uses all laser lines to participate in positioning. Each laser is emitting lasers and obtaining the scanning point cloud of the surrounding environment through all laser lines. However, in some environments, positioning can be performed without turning on all laser lines. Therefore, turning on all laser lines will cause unnecessary energy consumption. Summary of the invention

[0005] The embodiments of the present application provide a control method, device, electronic device and readable storage medium for a laser system, which can solve the problem of high energy consumption in existing positioning methods.

[0006] In a first aspect, an embodiment of the present application provides a control method for a laser system, comprising:

[0007] Get the point cloud map of the target area;

[0008] According to the walking track and installation information of the real radar, the simulated radar points are set in the point cloud map;

[0009] For each of the simulated radar points, performing a simulated radar scan on the simulated radar point to obtain a simulated single-frame point cloud of the simulated radar point;

[0010] After segmenting and feature classifying each of the single-frame point clouds, the positioning laser line is identified according to the segmentation results and classification results of each of the single-frame point clouds to obtain positioning laser line information, and the positioning laser line information is used to adjust the number of laser emissions of the real radar.

[0011] Furthermore, the performing a simulated radar scan on the simulated radar point to obtain a simulated single-frame point cloud of the simulated radar point includes:

[0012] Determining a scanning angle set of the simulated radar points according to the resolution of the real radar;

[0013] Taking the simulated radar point as the center point, obtaining a point cloud within a preset range;

[0014] Based on the spatial conversion relationship between the point cloud map coordinate system and the radar coordinate system, converting the point cloud to the radar coordinate system of the simulated radar point;

[0015] In the radar coordinate system, calculating the angle information of each point in the point cloud and the distance between the point and the simulated radar point;

[0016] Matching the angle information of each point with the scanning angle set to obtain a target point whose angle information matches the scanning angle in the scanning angle set;

[0017] For each of the target points, determining whether the target point is a point with the smallest distance under the angle information;

[0018] If yes, the target point is used as a scanning point;

[0019] If not, the target point is regarded as a non-scanning point;

[0020] The single-frame point cloud of the simulated radar point is composed based on each of the scanning points.

[0021] Further, the walking trajectory is composed of trajectory points;

[0022] Before converting the point cloud to the radar coordinate system of the simulated radar point, the method further includes:

[0023] Based on the simulated radar point, acquiring the trajectory point with the shortest distance to the simulated radar point;

[0024] Based on the trajectory points, the spatial conversion relationship between the point cloud map coordinate system and the radar coordinate system is obtained.

[0025] Furthermore, the segmentation and feature classification of each single-frame point cloud includes:

[0026] Dividing the single-frame point cloud into single-line point clouds according to the laser line information of the simulated radar point;

[0027] For each of the single-line point clouds, boundary segmentation, object size segmentation and ground segmentation are performed on the single-line point cloud to obtain a segmentation result of the single-line point cloud;

[0028] Performing corner point feature classification and surface point feature classification on the segmentation result of the single-line point cloud to obtain a classification result of the single-line point cloud;

[0029] The segmentation result of the single-frame point cloud includes the segmentation results of each of the single-line point clouds;

[0030] The classification result of the single-frame point cloud includes the classification results of each of the single-line point clouds.

[0031] Furthermore, the performing boundary segmentation, object size segmentation and ground segmentation on the single-line point cloud includes:

[0032] For each point in the single-line point cloud, calculating a first distance between the point and a previous point, and a second distance between the point and a subsequent point;

[0033] If it is determined that the preset distance condition is met according to the first distance and the second distance, the point is used as a boundary point of the object;

[0034] Segmenting the single-line point cloud according to the boundary points of the object and the continuity of the point cloud to obtain an object point cloud of each object;

[0035] Determining, according to the length of the object point cloud, a category to which the object point cloud belongs, wherein the category includes a large object point cloud and a small object point cloud;

[0036] If the minimum height of the large object point cloud meets the preset height condition, the large object point cloud is classified as a ground large object point cloud;

[0037] If the minimum height of the large object point cloud does not meet the preset height condition, classifying the large object point cloud as a non-ground large object point cloud;

[0038] If the minimum height of the small object point cloud meets the preset height condition, the small object point cloud is classified as a ground small object point cloud;

[0039] If the minimum height of the small object point cloud does not meet the preset height condition, the small object point cloud is classified as a non-ground small object point cloud.

[0040] Furthermore, determining the category of the object point cloud according to the length of the object point cloud includes:

[0041] Based on the radar coordinate system, finding the maximum and minimum values ​​of the x-axis, y-axis and z-axis in the object point cloud, and forming a maximum point and a minimum point, wherein the radar coordinate system includes an x-axis, a y-axis and a z-axis;

[0042] Calculating the distance between the maximum value point and the minimum value point to obtain the length of the object point cloud;

[0043] If the length of the object point cloud meets the preset length condition, dividing the object point cloud into the large object point cloud;

[0044] If the length of the object point cloud does not meet the preset length condition, the object point cloud is divided into the small object point cloud.

[0045] Furthermore, the identifying the positioning laser line according to the segmentation result and classification result of each single frame point cloud to obtain the positioning laser line information includes:

[0046] For each single-line point cloud in each single-frame point cloud, if the single-line point cloud includes the ground large object point cloud and surface points, the laser line corresponding to the single-line point cloud is determined as the positioning laser line;

[0047] When the single-line point cloud does not include the ground large object point cloud and the surface points, if the total number of points in the single-line point cloud is greater than or equal to the preset number of points, and the total number of feature points in the single-line point cloud accounts for a greater than the preset value, the laser line corresponding to the single-line point cloud is determined as the positioning laser line, and the total number of feature points includes the number of corner points and the number of surface points;

[0048] The positioning laser lines in each of the single-frame point clouds are counted to obtain the positioning laser line information.

[0049] Furthermore, according to the walking track and installation information of the real radar, the simulated radar point is set in the point cloud map, including:

[0050] Partitioning the point cloud map to obtain at least two map areas;

[0051] According to the walking track and installation information of the real radar, the simulated radar point is set in each of the map areas.

[0052] Furthermore, after segmenting and feature classifying each of the single-frame point clouds, the positioning laser line is identified according to the segmentation result and classification result of each of the single-frame point clouds to obtain the positioning laser line information, including:

[0053] For each of the image regions, segmenting and feature classifying each of the single-frame point clouds in the image region;

[0054] According to the segmentation result and classification result of each single frame point cloud, identifying the positioning laser line of each single frame point cloud;

[0055] The positioning laser lines of each of the single-frame point clouds in the image area are combined to obtain the positioning laser lines of the image area.

[0056] In a second aspect, an embodiment of the present application provides a control method for a laser system, comprising:

[0057] Acquiring position information of a real radar, and determining a target scanning area of ​​the real radar according to the position information of the real radar;

[0058] Acquiring positioning laser line information within the target scanning area;

[0059] According to the positioning laser line information, the number of laser emissions of the real radar is adjusted to scan the target scanning area.

[0060] In a third aspect, an embodiment of the present application provides a control device for a laser system, comprising:

[0061] An acquisition unit, used for acquiring a point cloud map of a target area;

[0062] A simulated radar processing unit, used to set at least one simulated radar point in the point cloud map according to the walking track and installation information of the real radar;

[0063] For each of the simulated radar points, performing a simulated radar scan on the simulated radar point to obtain a simulated single-frame point cloud of the simulated radar point;

[0064] The recognition unit is used to segment and feature classify each of the single-frame point clouds, and then identify the positioning laser line according to the segmentation results and classification results of each of the single-frame point clouds to obtain positioning laser line information, and the positioning laser line information is used to adjust the number of laser emissions of the real radar.

[0065] In a fourth aspect, an embodiment of the present application provides a control device for a laser system, comprising:

[0066] A real radar processing unit, used to obtain the position information of the real radar, and determine the target scanning area of ​​the real radar according to the position information of the real radar;

[0067] Used to obtain positioning laser line information within the target scanning area;

[0068] Used to adjust the number of laser emissions of the real radar according to the positioning laser line information to scan the target scanning area.

[0069] In a fifth aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method described in any one of the first aspect or the second aspect is implemented.

[0070] In a sixth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of the first aspect or the second aspect is implemented.

[0071] In a seventh aspect, an embodiment of the present application provides a computer program product, which, when executed on a terminal device, enables the terminal device to execute any one of the methods described in the first aspect or the second aspect.

[0072] It can be understood that the beneficial effects of the second to seventh aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0073] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0074] The embodiment of the present application obtains a point cloud map of the target area; sets simulated radar points in the point cloud map according to the walking trajectory and installation information of the real radar; performs a simulated radar scan on each simulated radar point to obtain a simulated single-frame point cloud of the simulated radar point; after segmenting and feature classifying each single-frame point cloud, identifies the positioning laser line according to the segmentation result and classification result of each single-frame point cloud, and obtains the positioning laser line information. The positioning laser line information is used to adjust the number of laser emissions of the real radar, and the positioning line attributes can be added to the map, so that the real radar can know in advance the emission laser lines that have little impact on positioning, so as to adjust the number of laser emissions of the real radar, thereby solving the unnecessary energy consumption in the positioning and mapping process and increasing the efficiency of positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0076] Figure 1 is a schematic diagram of the structure of a radar coordinate system provided by an embodiment of the present application;

[0077] Figure 2 is a flow chart of a control method of a laser system provided in one embodiment of the present application;

[0078] Figure 3 is a schematic diagram of points in a radar coordinate system provided by an embodiment of the present application;

[0079] Figure 4 is a schematic diagram of a structure of a grid for partitioning provided in an embodiment of the present application;

[0080] Figure 5 is a schematic diagram of the structure of a simulated radar point provided in an embodiment of the present application;

[0081] Figure 6is a schematic diagram of the structure of a simulated radar point provided by another embodiment of the present application;

[0082] Figure 7 is a schematic diagram of the structure of a simulated radar point provided by another embodiment of the present application;

[0083] Figure 8 is a flow chart of a control method of a laser system provided in another embodiment of the present application;

[0084] Fig. 9 is a schematic diagram of the structure of a control device for a laser system provided in one embodiment of the present application;

[0085] Fig.10 is a schematic structural diagram of a control device for a laser system provided in another embodiment of the present application;

[0086] Fig.11 It is a schematic diagram of the structure of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0087] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0088] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0089] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0090] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0091] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0092] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0093] The laser slam system uses all laser lines to participate in positioning. Each laser is emitting lasers and obtaining a scanning point cloud of the surrounding environment through all laser lines. The radar in the laser slam system corresponds to the real radar in the embodiment of the present application. The radar in the laser slam system can control the opening and closing of the laser by controlling the opening and closing of the switch. Figure 1 Schematic diagram of the structure of the radar coordinate system provided by an embodiment of the present application. Figure 1 As shown in the figure, the z-axis direction of the radar coordinate system is consistent with the rotation axis direction, and the z-axis direction is the vertical direction. In the z-axis direction, the angular interval between adjacent laser lines is the vertical resolution. The XOY plane of the radar coordinate system is the horizontal plane, and in the horizontal plane, the angular interval between the laser line at the previous moment and the laser line at the next moment is the horizontal resolution.

[0094] In complex environments, when positioning, there will be laser lines that are emitted into the air but cannot obtain point clouds or laser lines with few positioning features. These laser lines have little effect on positioning. However, the activation of these laser lines will lead to energy consumption of the laser slam system.

[0095] Based on the above problems, the embodiments of the present application provide a control method, device, electronic device and readable storage medium for a laser system.

[0096] Figure 2 FIG. 1 is a flow chart of a control method for a laser system provided in an embodiment of the present application. As an example and not a limitation, Figure 2 As shown, the method includes:

[0097] S101: Obtain a point cloud map of the target area.

[0098] S102: According to the movement track and installation information of the real radar, a simulated radar point is set in the point cloud map.

[0099] The installation information includes installation height, installation angle and other information.

[0100] Specifically, the number of simulated radar points set in the point cloud map may be the same as or different from the number of trajectory points of the real radar, and the overall shape of the set simulated radar points may be the same as or similar to the walking trajectory of the real radar, and the position of the simulated radar points on the point cloud map may correspond to the position of the real radar in the real scene.

[0101] S103: For each simulated radar point, perform a simulated radar scan on the simulated radar point to obtain a simulated single-frame point cloud of the simulated radar point.

[0102] Specifically, based on the radar scanning principle, the simulated radar points are scanned and simulated to obtain a single-frame point cloud.

[0103] S104: After segmenting and feature classifying each single-frame point cloud, identify the positioning laser line according to the segmentation result and classification result of each single-frame point cloud, and obtain positioning laser line information. The positioning laser line information is used to adjust the number of laser emissions of the real radar.

[0104] Specifically, firstly, the single-frame point cloud is divided into single-line point clouds according to the laser line information of the simulated radar points.

[0105] For example, if the real radar is a laser radar with 16 lasers, the laser line information of the simulated radar point has 16 laser lines. According to the 16 laser lines, the single-frame point cloud is divided into 16 single-line point clouds. For the convenience of subsequent processing, the 16 single-line point clouds can be numbered.

[0106] Next, for each single-line point cloud, boundary segmentation, object size segmentation and ground segmentation are performed on the single-line point cloud to obtain the segmentation result of the single-line point cloud.

[0107] For example, 16 single-line point clouds are segmented to obtain 16 segmentation results.

[0108] Then, the segmentation result of the single-line point cloud is subjected to corner point feature classification and surface point feature classification to obtain the classification result of the single-line point cloud.

[0109] For example, feature classification is performed on 16 segmentation results to obtain 16 classification results.

[0110] The segmentation result of the single-frame point cloud includes the segmentation results of each single-line point cloud; and the classification result of the single-frame point cloud includes the classification results of each single-line point cloud.

[0111] Finally, according to the segmentation and classification results of each single-frame point cloud, the positioning laser line is identified and the positioning laser line information is obtained, thereby obtaining a point cloud map of the target area carrying the positioning laser line information.

[0112] The point cloud map can be divided into at least one scanning area, and each scanning area contains corresponding positioning laser line information.

[0113] This embodiment obtains a point cloud map of the target area; sets simulated radar points in the point cloud map according to the walking trajectory and installation information of the real radar; performs simulated radar scanning on each simulated radar point to obtain a simulated single-frame point cloud of the simulated radar point; after segmenting and feature classifying each single-frame point cloud, identifies the positioning laser line according to the segmentation result and classification result of each single-frame point cloud, and obtains the positioning laser line information. The positioning laser line information is used to adjust the number of laser emissions of the real radar, and the positioning line attributes can be added to the map, so that the real radar can know in advance the emission laser lines that have little impact on positioning, so as to adjust the number of laser emissions of the real radar, thereby solving the unnecessary energy consumption in the positioning and mapping process and increasing the efficiency of positioning.

[0114] In another embodiment, performing a simulated radar scan on a simulated radar point to obtain a simulated single-frame point cloud of the simulated radar point includes:

[0115] First, according to the resolution of the real radar, the scanning angle set of the simulated radar points is determined;

[0116] Next, the simulated radar point is used as the center point to obtain the point cloud within the preset range;

[0117] Then, based on the spatial transformation relationship between the point cloud map coordinate system and the radar coordinate system, the point cloud is transformed into the radar coordinate system of the simulated radar point;

[0118] Next, in the radar coordinate system, the angle information of each point in the point cloud and the distance between it and the simulated radar point are calculated;

[0119] Then, the angle information of each point is matched with the scanning angle set to obtain a target point whose angle information matches the scanning angle in the scanning angle set;

[0120] Next, for each target point, determine whether the target point is the point with the smallest distance under the angle information;

[0121] If yes, the target point is used as the scanning point;

[0122] If not, the target point is regarded as a non-scanning point;

[0123] Finally, based on each scanning point, a single-frame point cloud of simulated radar points is composed.

[0124] For example, take a simulated radar point as an example: the real radar is a laser radar with 16 lasers, corresponding to 16 vertical angles β; the horizontal resolution is 0.2°, corresponding to 1800 horizontal angles α, then the scanning angle set of a simulated radar point has a total of 16×360 / 0.2=28800, including {(α 0 , β 0 ),...,(α i , β j )},

[0125] Next, taking the simulated radar point as the center, calculate the distance between each point in the point cloud and the simulated radar point, and discard the points whose distance is greater than the preset range, so as to obtain the point cloud within the preset range; then, subtract the simulated radar point from the point cloud to make the origin of the point cloud map coordinate system coincide with the origin of the radar coordinate system, and based on the spatial conversion relationship between the point cloud map coordinate system and the radar coordinate system, convert the point cloud to the radar coordinate system of the simulated radar point.

[0126] Next, calculate the angle information (horizontal angle α, vertical angle β) and distance r of each point. Figure 3 is a schematic diagram of the midpoint of the radar coordinate system provided by an embodiment of the present application, such as Figure 3 As shown in the figure, the coordinates of a point in the radar coordinate system are displayed, where r is the distance between the point and the origin of the coordinates. Then, the horizontal angle α and vertical angle β of each point are matched with the scanning angle in the scanning angle set to obtain the target point whose angle information matches the scanning angle in the scanning angle set; then, for each target point, it is determined whether the target point is the point with the smallest distance under the angle information, because the point with the smallest distance is the scanning point belonging to the simulated radar. If so, the target point is used as the scanning point; finally, based on each scanning point, a single-frame point cloud of the simulated radar point is formed to obtain a simulated single-frame point cloud of the simulated radar point.

[0127] To obtain a simulated single-frame point cloud of another simulated radar point, it is only necessary to replace the radar coordinate system with the radar coordinate system of the other simulated radar point, and the other steps remain unchanged.

[0128] This embodiment determines the scanning angle set of simulated radar points according to the resolution of the real radar, obtains the target point whose angle information matches the scanning angle in the scanning angle set, judges for each target point whether the target point is the point with the minimum distance under the angle information, and composes a single-frame point cloud of the simulated radar point based on each scanning point, thereby improving the accuracy of the simulated scanning of the simulated radar point, thereby obtaining an accurate single-frame point cloud of the simulated radar point.

[0129] In another embodiment, the walking trajectory is composed of trajectory points;

[0130] Before converting the point cloud to the radar coordinate system of the simulated radar point, it also includes:

[0131] First, based on the simulated radar point, obtain the trajectory point with the shortest distance to the simulated radar point;

[0132] Then, based on the trajectory points, the spatial transformation relationship between the point cloud map coordinate system and the radar coordinate system is obtained.

[0133] This embodiment obtains the accurate spatial conversion relationship by obtaining the trajectory point with the shortest distance to the simulated radar point and obtaining the spatial conversion relationship between the point cloud map coordinate system and the radar coordinate system based on the trajectory point.

[0134] In another embodiment, boundary segmentation, object size segmentation and ground segmentation are performed on a single-line point cloud, including:

[0135] First, for each point in the single-line point cloud, a first distance between the point and the previous point, and a second distance between the point and the next point are calculated.

[0136] For example, a single-line point cloud contains a point set {P1, P2, P3, .., Pn}, and a first distance dis1 between point Pi and point Pi-1 is calculated, and a second distance dis2 between point Pi and point Pi+1 is calculated.

[0137] Next, if it is determined that the preset distance condition is met according to the first distance and the second distance, the point is taken as a boundary point of the object.

[0138] For example, the preset distance condition is |dis1|>2×|dis2| or |dis2|>2×|dis1|. If the first distance and the second distance meet |dis1|>2×|dis2| or |dis2|>2×|dis1|, then the point Pi is a boundary point of the object.

[0139] Then, the single-line point cloud is segmented according to the object boundary points and point cloud continuity to obtain the object point cloud of each object.

[0140] Next, according to the length of the object point cloud, the category to which the object point cloud belongs is determined, and the categories include large object point cloud and small object point cloud.

[0141] Specifically, based on the radar coordinate system, the maximum and minimum values ​​of the x-axis, y-axis and z-axis in the object point cloud are found, and the maximum value point and the minimum value point are formed. The radar coordinate system includes the x-axis, y-axis and z-axis;

[0142] Calculate the distance between the maximum and minimum points to obtain the length of the object point cloud;

[0143] After the distance between the maximum value point and the distance between the minimum value point are obtained, the length of the object point cloud is calculated based on the distance between the maximum value point and the distance between the minimum value point.

[0144] Then, if the length of the object point cloud meets the preset length condition, the object point cloud is divided into a large object point cloud;

[0145] For example, the preset length condition is set to 6 m, but is not limited thereto. If the length of the object point cloud is greater than 6 m, the object point cloud is divided into a large object point cloud.

[0146] If the length of the object point cloud does not meet the preset length condition, the object point cloud is divided into a small object point cloud.

[0147] For example, if the length of the object point cloud is less than 6m, the object point cloud is divided into a small object point cloud.

[0148] If the minimum height of the large object point cloud meets the preset height condition, the large object point cloud is classified as a ground large object point cloud.

[0149] For example, the preset height condition is z min <0,|z min +h|≤0, h is the actual radar installation height. If the minimum height z min Comply with z min <0,|z min +h|≤0, the large object point cloud is divided into ground large object point cloud.

[0150] If the minimum height of the large object point cloud does not meet the preset height condition, the large object point cloud is classified as a non-ground large object point cloud.

[0151] For example, if the minimum height z min Does not meet z min <0,|z min +h|≤0, the large object point cloud is divided into non-ground large object point cloud.

[0152] If the minimum height of the small object point cloud meets the preset height condition, the small object point cloud is classified as a ground small object point cloud.

[0153] For example, if the minimum height z min Comply with z min <0,|z min +h|≤0, the small object point cloud is divided into ground small object point cloud.

[0154] If the minimum height of the small object point cloud does not meet the preset height condition, the small object point cloud is classified as a non-ground small object point cloud.

[0155] For example, if the minimum height z min Does not meet zmin <0,|z min +h|≤0, the small object point cloud is divided into non-ground small object point cloud.

[0156] This embodiment determines that the preset distance condition is met based on the first distance and the second distance, and then uses the point as the object boundary point, and accurately divides the category to which the object point cloud belongs based on whether the length of the object point cloud meets the preset length condition and whether it meets the preset height condition.

[0157] In another embodiment, the segmentation result of the single-line point cloud is subjected to corner point feature classification and surface point feature classification to obtain the classification result of the single-line point cloud, including:

[0158] First, calculate the curvature of each point in the segmentation result;

[0159] Then, corner point feature classification and surface point feature classification are performed according to the curvature.

[0160] For example, the segmentation result includes an object point cloud, and the curvature of each point in the object point cloud is calculated. For each point, based on the curvature, if the size difference, curvature and smoothness of the point and the surrounding points are all lower than the corresponding preset values, the point is a plane point; if the size difference, curvature and smoothness of the point and the surrounding points are all higher than the corresponding preset values, the point is a corner point.

[0161] In another embodiment, according to the segmentation result and classification result of each single frame point cloud, the positioning laser line of the image area is identified to obtain the positioning laser line information, including:

[0162] First, for each single-line point cloud in each single-frame point cloud, if the single-line point cloud includes large ground object point clouds and surface points, the laser line corresponding to the single-line point cloud is determined as the positioning laser line.

[0163] Then, when the single-line point cloud does not include large ground object point clouds and surface points, if the total number of points in the single-line point cloud is greater than or equal to the preset number of points, and the total number of feature points in the single-line point cloud accounts for a greater than the preset value, the laser line corresponding to the single-line point cloud is determined as the positioning laser line, and the total number of feature points includes the number of corner points and the number of surface points.

[0164] Among them, 20% of the points in a real radar scan can be used as the preset points, and 40% of the total number of feature points in the total number of points can be used as the preset proportion value.

[0165] For example, the horizontal resolution of the actual radar is 0.2°, corresponding to 1800 points in one circle of laser line scanning, and the preset number of points is 360.

[0166] If the total number of points of the single-line point cloud is greater than or equal to 360, and the total number of feature points accounts for more than 40%, the laser line corresponding to the single-line point cloud is determined as the positioning laser line.

[0167] Finally, the positioning laser lines in each single-frame point cloud are counted to obtain the positioning laser line information.

[0168] In this embodiment, if a single-line point cloud includes point clouds of large objects on the ground and surface points, the laser line corresponding to the single-line point cloud is determined as the positioning laser line; if the total number of points in the single-line point cloud is greater than or equal to the preset number of points, and the proportion of the total number of feature points in the single-line point cloud is greater than the preset proportion value, the laser line corresponding to the single-line point cloud is determined as the positioning laser line, and the positioning laser lines in each single-frame point cloud are counted to obtain the positioning laser lines in the image area, so that the positioning laser lines of the single-frame point cloud can be accurately obtained.

[0169] In another embodiment, according to the walking track and installation information of the real radar, setting the simulated radar point in the point cloud map includes:

[0170] First, the point cloud map is partitioned to obtain at least two regions.

[0171] Figure 4 is a schematic diagram of a grid structure for partitioning provided by an embodiment of the present application. Figure 4 As shown, the xoy coordinate system is established, and based on the xoy plane, the plane is segmented according to the preset grid size to obtain a grid map. The size of the grid can be set according to the actual application scenario, application requirements or hardware configuration. For example, the grid size is set to 20-40 meters. The number of grids in the x-axis direction and the number of grids in the y-axis direction can be set according to the actual application scenario, application requirements or hardware configuration.

[0172] After obtaining the point cloud map, an Xoy coordinate system is established on the point cloud map, and plane segmentation is performed according to the preset grid size to realize the partitioning of the point cloud map.

[0173] Next, according to the movement track and installation information of the real radar, simulated radar points are set in each map area.

[0174] Set simulated radar points in the map area according to actual application scenarios and application requirements. Figure 5 Schematic diagram of the structure of the simulated radar point provided by an embodiment of the present application. Figure 5 As shown, the walking track 10 of the real radar is a straight track. For each map area, according to the straight track and installation information of the real radar in the map area, continuous simulated radar points are set up. The walking track 11 of the simulated radar point is the same as the straight track. The walking track 11 of the simulated radar point passes through the center of the map area, providing a basis for better determining the positioning laser line later; the number of simulated radar points can be the same as the number of track points of the real radar in the map area, or it can be different.

[0175] or, Figure 6is a schematic diagram of the structure of a simulated radar point provided by another embodiment of the present application. Figure 6 As shown, the walking track 20 of the real radar includes a straight track and a curved track. If the walking track 20 of the real radar in the image area only has a straight track, then a continuous simulated radar point is set up according to the straight track and the installation information. The walking track 21 of the simulated radar point is the same as the straight track. The walking track 21 of the simulated radar point passes through the center of the image area, providing a basis for better determining the positioning laser line later; the number of simulated radar points can be the same as the number of track points of the real radar in the image area, or it can be different.

[0176] If the actual radar's walking track 20 in the image area includes a straight track and a curved track, a continuous simulated radar point is set up according to the straight track, the curved track and the installation information. The walking track 21 of the simulated radar point is the same as the straight track and the curved track; the straight part of the walking track 21 of the simulated radar point passes through the center of the image area, or the center of the curved part of the walking track 21 of the simulated radar point passes through the center of the image area, providing a basis for better determining the positioning laser line later; the number of simulated radar points can be the same as the number of track points of the actual radar in the image area, or it can be different.

[0177] If the real radar in the image area has only a curved track, continuous simulated radar points are set up according to the curved track and installation information. The simulated radar point's track 21 is the same as the curved track, and the center of the simulated radar point's track 21 passes through the center of the image area, providing a basis for better determining the positioning laser line later; the number of simulated radar points can be the same as or different from the number of track points of the real radar in the image area.

[0178] or, Figure 7 is a schematic diagram of the structure of a simulated radar point provided by another embodiment of the present application. Figure 7 As shown, the real radar's walking track 30 is a straight track, but it only exists in part of the map area. If there is a real radar's walking track 30 in the map area, a continuous simulated radar point is set up according to the straight track and installation information. The walking track 31 of the simulated radar point is the same as the straight track. The walking track 31 of the simulated radar point passes through the center of the map area, providing a basis for better determining the positioning laser line later; the number of simulated radar points can be the same as the number of track points of the real radar in the map area, or it can be different.

[0179] If there is no real radar walking track 30 in the map area, it is not necessary to set a simulated radar point, or it is possible to set a simulated radar point. To provide a basis for better determining the positioning laser line in the future, set a simulated radar point. First, determine the map area with the walking track 30 closest to the map area, and then set up continuous simulated radar points based on the straight line track and installation information of the nearest map area. The walking track 31 of the simulated radar point is the same as the straight line track, and the walking track 31 of the simulated radar point passes through the center of the map area; the number of simulated radar points can be the same as the number of track points of the real radar in the map area, or it can be different.

[0180] Among them, the walking trajectory of the simulated radar point may not pass through the center of the map area.

[0181] In another embodiment, after segmenting and feature classifying each single frame point cloud, the positioning laser line is identified according to the segmentation result and classification result of each single frame point cloud to obtain the positioning laser line information, including:

[0182] First, for each image area, segment and feature classify each single-frame point cloud in the image area;

[0183] Next, according to the segmentation result and classification result of each single frame point cloud, the positioning laser line of each single frame point cloud is identified;

[0184] Then, the positioning laser lines of each single-frame point cloud in the image area are combined to obtain the positioning laser line information of the image area.

[0185] Figure 8 FIG. 1 is a flow chart of a control method of a laser system provided by another embodiment of the present application. As an example and not a limitation, Figure 8 As shown, the method includes:

[0186] S201: Acquire the position information of the real radar, and determine the target scanning area of ​​the real radar according to the position information of the real radar.

[0187] The point cloud map carrying the positioning laser line information of the target area is pre-stored, and the point cloud map includes at least one scanning area, and each scanning area includes corresponding positioning laser line information. The point cloud map carrying the positioning laser line information is obtained by the above-mentioned various method embodiments.

[0188] Specifically, during the actual positioning process, the real radar obtains the position information of the real radar in real time, and then determines the target scanning area based on the position information.

[0189] S202: Acquire positioning laser line information within the target scanning area.

[0190] Specifically, according to the target scanning area, the corresponding positioning laser line information is obtained.

[0191] S203: According to the positioning laser line information, the number of laser emissions of the real radar is adjusted to scan the target scanning area.

[0192] Specifically, based on the obtained positioning laser line information, the laser of the real radar is controlled to be turned on and off to adjust the number of laser emissions, and the target scanning area is scanned using the laser in the turned-on state.

[0193] This embodiment obtains the position information of the real radar, determines the target scanning area of ​​the real radar based on the position information of the real radar, obtains the positioning laser line information in the target scanning area, and adjusts the laser emission number of the real radar based on the positioning laser line information to scan the target scanning area, thereby adjusting the laser emission number of the real radar scanning the target scanning area, thereby reducing unnecessary energy loss, reducing the amount of calculation and load.

[0194] In another embodiment, the point cloud map is divided into at least two regions, each region contains corresponding positioning laser line information, and the scanning area corresponds to the region.

[0195] The method comprises:

[0196] First, the position information of the real radar is obtained, and based on the position information of the real radar, the target map area where the real radar is located is determined.

[0197] Next, the positioning laser line information of the target area is obtained.

[0198] Then, according to the positioning laser line information, the number of laser emissions of the real radar is adjusted to scan the target area.

[0199] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0200] Corresponding to the method described in the above embodiment, for the convenience of explanation, only the part related to the embodiment of the present application is shown.

[0201] Fig. 9 Schematic diagram of the structure of a control device for a laser system provided in one embodiment of the present application. As an example and not a limitation, Fig. 9 As shown, the device comprises:

[0202] An acquisition unit 40 is used to acquire a point cloud map of a target area;

[0203] The simulated radar processing unit 41 is used to set simulated radar points in the point cloud map according to the walking track and installation information of the real radar;

[0204] For each simulated radar point, a simulated radar scan is performed on the simulated radar point to obtain a simulated single-frame point cloud of the simulated radar point;

[0205] The identification unit 42 is used to segment and feature classify each single-frame point cloud, and then identify the positioning laser line according to the segmentation result and classification result of each single-frame point cloud to obtain the positioning laser line information, and the positioning laser line information is used to adjust the laser emission number of the real radar.

[0206] In another embodiment, the simulated radar processing unit is specifically used to determine a set of scanning angles of simulated radar points according to a resolution of a real radar;

[0207] Used to obtain point clouds within a preset range using the simulated radar point as the center point;

[0208] It is used to transform the point cloud into the radar coordinate system of the simulated radar point based on the spatial transformation relationship between the point cloud map coordinate system and the radar coordinate system;

[0209] Used to calculate the angle information of each point in the point cloud and the distance between it and the simulated radar point in the radar coordinate system;

[0210] Used to match the angle information of each point with the scanning angle set to obtain a target point whose angle information matches the scanning angle in the scanning angle set;

[0211] Used to determine, for each target point, whether the target point is the point with the smallest distance under the angle information;

[0212] If yes, the target point is used as the scanning point;

[0213] If not, the target point is regarded as a non-scanning point;

[0214] Used to compose a single-frame point cloud of simulated radar points based on various scanning points.

[0215] In another embodiment, the walking trajectory is composed of trajectory points;

[0216] The simulated radar processing unit is further used to obtain a trajectory point with the shortest distance to the simulated radar point based on the simulated radar point;

[0217] Based on the trajectory points, the spatial transformation relationship between the point cloud map coordinate system and the radar coordinate system is obtained.

[0218] In another embodiment, the recognition unit is specifically configured to divide the single-frame point cloud into single-line point clouds according to the laser line information of the simulated radar point;

[0219] It is used to perform boundary segmentation, object size segmentation and ground segmentation on each single-line point cloud to obtain the segmentation result of the single-line point cloud;

[0220] It is used to perform corner point feature classification and surface point feature classification on the segmentation result of the single-line point cloud to obtain the classification result of the single-line point cloud;

[0221] The segmentation results of a single-frame point cloud include the segmentation results of each single-line point cloud;

[0222] The classification results of a single-frame point cloud include the classification results of each single-line point cloud.

[0223] In another embodiment, the recognition unit is specifically configured to calculate, for each point in the single-line point cloud, a first distance between the point and a previous point, and a second distance between the point and a subsequent point;

[0224] for taking the point as a boundary point of the object if it is determined that the preset distance condition is met according to the first distance and the second distance;

[0225] It is used to segment the single-line point cloud according to the boundary points of the object and the continuity of the point cloud to obtain the object point cloud of each object;

[0226] It is used to determine the category of the object point cloud according to the length of the object point cloud, which includes large object point cloud and small object point cloud;

[0227] Used to classify the large object point cloud as a ground large object point cloud if the minimum height of the large object point cloud meets the preset height condition;

[0228] Used to classify the large object point cloud as a non-ground large object point cloud if the minimum height of the large object point cloud does not meet the preset height condition;

[0229] Used to classify the small object point cloud as a ground small object point cloud if the minimum height of the small object point cloud meets the preset height condition;

[0230] If the minimum height of the small object point cloud does not meet the preset height condition, the small object point cloud is classified as a non-ground small object point cloud.

[0231] In another embodiment, the identification unit is specifically used to find the maximum and minimum values ​​of the x-axis, y-axis and z-axis in the object point cloud based on the radar coordinate system, and form the maximum value point and the minimum value point, and the radar coordinate system includes the x-axis, the y-axis and the z-axis;

[0232] Used to calculate the distance between the maximum point and the minimum point to obtain the length of the object point cloud;

[0233] Used to divide the object point cloud into large object point clouds if the length of the object point cloud meets the preset length condition;

[0234] If the length of the object point cloud does not meet the preset length condition, the object point cloud will be divided into small object point clouds.

[0235] In another embodiment, the recognition unit is specifically configured to, for each single-line point cloud in each single-frame point cloud, determine the laser line corresponding to the single-line point cloud as the positioning laser line if the single-line point cloud includes a large ground object point cloud and a surface point;

[0236] When the single-line point cloud does not include large ground object point clouds and surface points, if the total number of points in the single-line point cloud is greater than or equal to the preset number of points, and the total number of feature points in the single-line point cloud accounts for a greater than the preset value, the laser line corresponding to the single-line point cloud is determined as the positioning laser line, and the total number of feature points includes the number of corner points and surface points;

[0237] It is used to count the positioning laser lines in each single-frame point cloud and obtain the positioning laser line information.

[0238] In another embodiment, the simulated radar processing unit is specifically used to partition the point cloud map to obtain at least two map areas;

[0239] According to the movement track and installation information of the real radar, simulated radar points are set in each map area.

[0240] In another embodiment, the recognition unit is used to segment and feature classify each single-frame point cloud in each image region;

[0241] According to the segmentation result and classification result of each single frame point cloud, identify the positioning laser line of each single frame point cloud;

[0242] The positioning laser lines of each single-frame point cloud in the image area are combined to obtain the positioning laser lines of the image area.

[0243] Fig.10 is a schematic diagram of the structure of a control device for a laser system provided in another embodiment of the present application. As an example and not a limitation, Fig.10 As shown, the device comprises:

[0244] The first information acquisition unit 50 is used to acquire the position information of the real radar and determine the target scanning area of ​​the real radar according to the position information of the real radar;

[0245] The second information acquisition unit 51 is used to acquire the positioning laser line information in the target scanning area;

[0246] The real radar adjustment unit 52 is used to adjust the number of laser emissions of the real radar according to the positioning laser line information to scan the target scanning area.

[0247] Fig.11 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Fig.11 As shown, the electronic device 6 of this embodiment includes: at least one processor 60 ( Fig.11Only one is shown in the figure), a memory 61, and a computer program 62 stored in the memory 61 and executable on the at least one processor 60, wherein the processor 60 implements the steps of any of the above-mentioned method embodiments when executing the computer program 62.

[0248] The electronic device 6 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device 6 may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will appreciate that Fig.11 It is only an example of the electronic device 6 and does not constitute a limitation on the electronic device 6. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, etc.

[0249] The processor 60 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0250] In some embodiments, the memory 61 may be an internal storage unit of the electronic device 6, such as a hard disk or memory of the electronic device 6. In other embodiments, the memory 61 may also be an external storage device of the electronic device 6, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 6. Further, the memory 61 may also include both an internal storage unit of the electronic device 6 and an external storage device. The memory 61 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program, etc. The memory 61 may also be used to temporarily store data that has been output or is to be output.

[0251] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0252] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0253] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.

[0254] An embodiment of the present application provides a computer program product. When the computer program product runs on a mobile terminal, the mobile terminal can implement the steps in the above-mentioned method embodiments when executing the computer program product.

[0255] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0256] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0257] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0258] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0259] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0260] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0261] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0262] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0263] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0264] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A control method for a laser system, characterized in that, it includes: Obtain a point cloud map of the target area; According to the walking trajectory and installation information of the real radar, set simulated radar points in the point cloud map; For each of the simulated radar points, perform simulated radar scanning on the simulated radar point to obtain a single-frame point cloud of the simulation of the simulated radar point; After segmenting and feature-classifying each of the single-frame point clouds, according to the segmentation result and classification result of each of the single-frame point clouds, identify and locate the laser line to obtain laser line information for adjusting the laser emission number of the real radar.

2. The method according to claim 1, characterized in that, The performing simulated radar scanning on the simulated radar point to obtain a single-frame point cloud of the simulation of the simulated radar point includes: Determine the scanning angle set of the simulated radar point according to the resolution of the real radar; Taking the simulated radar point as the center point, obtain the point cloud within a preset range; Based on the spatial conversion relationship between the point cloud map coordinate system and the radar coordinate system, convert the point cloud to the radar coordinate system of the simulated radar point; In the radar coordinate system, calculate the angle information of each point in the point cloud and the distance from the point to the simulated radar point; Match the angle information of each point with the scanning angle set to obtain target points whose angle information matches the scanning angles in the scanning angle set; For each of the target points, determine whether the target point is the point with the smallest distance at the angle information; If so, take the target point as the scanning point; If not, take the target point as a non-scanning point; Based on each of the scanning points, form the single-frame point cloud of the simulated radar point.

3. The method according to claim 2, characterized in that, The walking trajectory is composed of trajectory points; Before converting the point cloud to the radar coordinate system of the simulated radar point, it further includes: Based on the simulated radar point, obtain the trajectory point with the shortest distance to the simulated radar point; Based on the trajectory point, obtain the spatial conversion relationship between the point cloud map coordinate system and the radar coordinate system.

4. The method according to claim 1, characterized in that, The segmenting and feature-classifying each of the single-frame point clouds includes: According to the laser line information of the simulated radar point, divide the single-frame point cloud into single-line point clouds; For each of the single-line point clouds, perform boundary segmentation, object size segmentation and ground segmentation on the single-line point cloud to obtain the segmentation result of the single-line point cloud; Perform corner feature classification and surface feature classification on the segmentation result of the single-line point cloud to obtain the classification result of the single-line point cloud; The segmentation result of the single-frame point cloud includes the segmentation results of each of the single-line point clouds; The classification result of the single-frame point cloud includes the classification results of each of the single-line point clouds.

5. The method according to claim 4, characterized in that, The performing boundary segmentation, object size segmentation and ground segmentation on the single-line point cloud includes: For each point in the single-line point cloud, calculating a first distance between the point and a previous point, and a second distance between the point and a subsequent point; If it is determined that the preset distance condition is met according to the first distance and the second distance, the point is used as a boundary point of the object; Segmenting the single-line point cloud according to the boundary points of the object and the continuity of the point cloud to obtain an object point cloud of each object; Determining, according to the length of the object point cloud, a category to which the object point cloud belongs, wherein the category includes a large object point cloud and a small object point cloud; If the minimum height of the large object point cloud meets the preset height condition, the large object point cloud is classified as a ground large object point cloud; If the minimum height of the large object point cloud does not meet the preset height condition, classifying the large object point cloud as a non-ground large object point cloud; If the minimum height of the small object point cloud meets the preset height condition, the small object point cloud is classified as a ground small object point cloud; If the minimum height of the small object point cloud does not meet the preset height condition, the small object point cloud is classified as a non-ground small object point cloud.

6. The method according to claim 5, It is characterized in that The step of determining the category of the object point cloud according to the length of the object point cloud comprises: Based on the radar coordinate system, finding the maximum and minimum values ​​of the x-axis, y-axis and z-axis in the object point cloud, and forming a maximum point and a minimum point, wherein the radar coordinate system includes an x-axis, a y-axis and a z-axis; Calculating the distance between the maximum value point and the minimum value point to obtain the length of the object point cloud; If the length of the object point cloud meets the preset length condition, dividing the object point cloud into the large object point cloud; If the length of the object point cloud does not meet the preset length condition, the object point cloud is divided into the small object point cloud.

7. The method according to claim 5, It is characterized in that The step of identifying the positioning laser line according to the segmentation result and classification result of each single frame point cloud and obtaining the positioning laser line information includes: For each single-line point cloud in each single-frame point cloud, if the single-line point cloud includes the ground large object point cloud and surface points, the laser line corresponding to the single-line point cloud is determined as the positioning laser line; When the single-line point cloud does not include the ground large object point cloud and the surface points, if the total number of points in the single-line point cloud is greater than or equal to the preset number of points, and the total number of feature points in the single-line point cloud accounts for a greater than the preset value, the laser line corresponding to the single-line point cloud is determined as the positioning laser line, and the total number of feature points includes the number of corner points and the number of surface points; The positioning laser lines in each of the single-frame point clouds are counted to obtain the positioning laser line information.

8. The method according to claim 1, It is characterized in that According to the walking track and installation information of the real radar, the simulated radar points are set in the point cloud map, including: Partitioning the point cloud map to obtain at least two map areas; According to the walking track and installation information of the real radar, the simulated radar point is set in each of the map areas.

9. The method according to claim 8, It is characterized in that After segmenting and feature classifying each of the single-frame point clouds, identifying the positioning laser line according to the segmentation result and classification result of each of the single-frame point clouds, and obtaining the positioning laser line information, including: For each of the image regions, segmenting and feature classifying each of the single-frame point clouds in the image region; According to the segmentation result and classification result of each single frame point cloud, identifying the positioning laser line of each single frame point cloud; The positioning laser lines of each of the single-frame point clouds in the image area are combined to obtain the positioning laser line information of the image area.

10. A method for controlling a laser system, It is characterized in that include: Acquire the position information of the real radar, and determine the target scanning area of ​​the real radar according to the position information of the real radar; Acquiring positioning laser line information within the target scanning area; According to the positioning laser line information, the number of laser emissions of the real radar is adjusted to scan the target scanning area.

11. A control device for a laser system, It is characterized in that include: An acquisition unit, used for acquiring a point cloud map of a target area; A simulated radar processing unit, used to set at least one simulated radar point in the point cloud map according to the walking track and installation information of the real radar; For each of the simulated radar points, performing a simulated radar scan on the simulated radar point to obtain a simulated single-frame point cloud of the simulated radar point; The recognition unit is used to segment and feature classify each of the single-frame point clouds, and then identify the positioning laser line according to the segmentation results and classification results of each of the single-frame point clouds to obtain positioning laser line information, and the positioning laser line information is used to adjust the number of laser emissions of the real radar.

12. A control device for a laser system, It is characterized in that include: A first information acquisition unit, used to acquire position information of a real radar, and determine a target scanning area of ​​the real radar according to the position information of the real radar; A second information acquisition unit, used to acquire positioning laser line information within the target scanning area; The real radar adjustment unit is used to adjust the number of laser emissions of the real radar according to the positioning laser line information to scan the target scanning area.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, the method according to any one of claims 1 to 9 or claim 10 is implemented.

14. A computer-readable storage medium storing a computer program. It is characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 9 or claim 10 is implemented.

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