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Obstacle identification method and system based on 3D laser point cloud

An obstacle recognition and laser point cloud technology, applied in the field of obstacle detection, can solve the problems of inability to meet the needs of indoor and outdoor three-dimensional complex environment obstacle avoidance, high obstacle false detection rate, and reduced accuracy, so as to improve the efficiency of point cloud segmentation , the effect of reducing the search range and improving the processing efficiency

Pending Publication Date: 2021-11-12
SHANDONG UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The inventors found that in the prior art, when ground segmentation and point cloud clustering are performed, all point clouds are traversed, or the ground is fitted iteratively, resulting in poor real-time performance, and the accuracy decreases as the distance increases. This leads to a high rate of false detection of obstacles, which cannot meet the needs of obstacle avoidance in indoor and outdoor three-dimensional complex environments.

Method used

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  • Obstacle identification method and system based on 3D laser point cloud
  • Obstacle identification method and system based on 3D laser point cloud
  • Obstacle identification method and system based on 3D laser point cloud

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Embodiment 1

[0039] Such as figure 1 As shown, Embodiment 1 of the present disclosure provides an obstacle recognition method based on a 3D laser point cloud, including the following process:

[0040] S1: Obtain 3D environment laser point cloud data, based on preprocessing, circumferential and radial rasterization processing of 3D environment laser point cloud data, to achieve efficient real-time ground segmentation;

[0041] S2: By processing the segmented non-terrestrial laser point cloud, two-dimensional European clustering is used to mark obstacles in each area;

[0042] S3: Through the cuboid model, the clustering is visualized and packaged to obtain the position and size of obstacles, so as to realize accurate identification of obstacles.

[0043] In S1, it specifically includes:

[0044] S1.1: Use multi-line lidar to obtain the original point cloud data of the 3D environment. Since the number of point clouds is very large, the original point cloud is preprocessed by voxel downsamp...

Embodiment 2

[0065] Embodiment 2 of the present disclosure provides an obstacle recognition system based on 3D laser point cloud, including:

[0066] The data acquisition module is configured to: acquire laser point cloud data of the three-dimensional environment;

[0067] The point cloud processing module is configured to: perform ground segmentation processing on the three-dimensional environment laser point cloud data, and obtain non-ground laser point cloud data;

[0068] The point cloud clustering module is configured to: partition non-terrestrial laser point cloud data, and use two-dimensional European clustering to mark obstacles in each partition;

[0069] The obstacle identification module is configured to: use a cuboid model to package the clustering results to obtain the position and size of the obstacle.

[0070] The working method of the system is the same as the obstacle recognition method based on the 3D laser point cloud provided in Embodiment 1, and will not be repeated h...

Embodiment 3

[0072] Embodiment 3 of the present disclosure provides a computer-readable storage medium, on which a program is stored. When the program is executed by a processor, the method of obstacle recognition based on 3D laser point cloud as described in Embodiment 1 of the present disclosure is implemented. step.

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Abstract

The invention provides an obstacle identification method and system based on 3D laser point cloud. The method comprises the following steps: acquiring three-dimensional environment laser point cloud data; performing ground segmentation processing on the three-dimensional environment laser point cloud data to obtain non-ground laser point cloud data; partitioning the non-ground laser point cloud data, and marking obstacles in each partition by using two-dimensional Euclidean clustering; and performing packaging processing on the clustering result by using a cuboid model to obtain the position and the size of an obstacle. According to the invention, the real-time performance of ground segmentation and point cloud clustering is effectively improved, and the identification precision of obstacles at a relatively long distance is improved.

Description

technical field [0001] The present disclosure relates to the technical field of obstacle detection, in particular to an obstacle recognition method and system based on 3D laser point cloud. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art. [0003] With the rapid development of unmanned driving technology and 3D laser SLAM (Simultaneous Localization And Mapping, simultaneous positioning and mapping) technology, the map construction based on 3D lidar is developing rapidly. The carrier uses the lidar point cloud information to obtain the orientation of obstacles Information, to achieve precise obstacle avoidance of the carrier. Obstacle detection based on laser point cloud can be divided into two steps: first, segment and remove the ground point cloud, so that each obstacle point cloud exists away from the ground; then, use the clustering algorithm ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S17/93
CPCG01S17/93Y02A90/10
Inventor 皇攀凌李留昭周军赵一凡林乐彬欧金顺高新彪孟广辉
Owner SHANDONG UNIV
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