Laser radar point cloud simulation method and device and computer equipment
A technology of lidar and simulation method, applied in the field of sensor simulation, can solve the problems of high cost, low efficiency of point cloud simulation of lidar and lidar, etc., and achieve the effect of improving simulation efficiency and reducing simulation cost.
Pending Publication Date: 2022-07-22
SHENZHEN DEEPROUTE AI CO LTD
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Problems solved by technology
The first type of method usually uses a mature large-scale game engine for point cloud rendering, and the second type of method uses a CPU for point cloud simulation, because neither of them considers lidar, especially the most widely used mechanical lidar at the same time. The characteristics of emitting multiple wire bundles (up to 64 or even 128 wires), so there are problems of low simulation efficiency and high cost of lidar point clouds
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[0054] In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, but not to limit the present application.
[0055] The lidar point cloud simulation method provided in the embodiment of the present application can be applied to, for example, figure 1in the application environment shown. The terminal 102 communicates with the server 104 through the network. The data storage system may store data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network server.
[0056] The present application can be applied to the terminal 102 or the server 104. The terminal 102 is used for illustrati...
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The invention relates to a laser radar point cloud simulation method and device and computer equipment. The method comprises the steps that a first processor obtains the position and posture of a target object; the second processor determines first grid data of the target object based on the position and the attitude; the second processor determines second grid data from the first grid data based on a target scanning range of the laser radar; the second processor determines a target polygon intersecting with a laser beam in the laser beam data in the target scanning range and coordinates of an intersection point intersecting with the laser beam in the second grid data; the second processor calculates the reflected point cloud intensity based on the direction vector information of the laser beam, the normal vector information of the target polygon and the intersection point coordinates, and the second processor determines the point cloud data corresponding to the target object in the target scanning range based on the point cloud intensity and the intersection point coordinates. By adopting the method, the simulation efficiency of the laser radar point cloud can be improved.
Description
technical field [0001] The present application relates to the technical field of sensor simulation, and in particular, to a method, device and computer equipment for LiDAR point cloud simulation. Background technique [0002] Lidar can provide accurate environmental depth measurements, so it is widely used in environmental perception and positioning tasks. Lidar is an important part of the autonomous driving sensor system, and the simulation of point cloud data is an indispensable part of the data closed loop of the Lidar perception algorithm. [0003] The existing LiDAR point cloud simulation technology is mainly divided into two categories, one is the GPU rendering method based on the game engine, and the other is the simulation method based on the CPU. The first type of method usually uses a mature large-scale game engine for point cloud rendering, and the second type of method uses CPU for point cloud simulation, because both of them do not consider lidar, especially th...
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Patent Timeline
Login to View More IPC IPC(8): G06F30/20G01S7/497G01S17/931G06F119/02
CPCG06F30/20G01S17/931G01S7/497G06F2119/02
Inventor 徐勋农
Owner SHENZHEN DEEPROUTE AI CO LTD