A Target Detection Algorithm for 3D Lidar Point Cloud

Author(s):  
Yin Zhang ◽  
Guoquan Ren ◽  
Ziyang Cheng ◽  
Guojie Kong
2021 ◽  
Author(s):  
Zhiguo Zhou ◽  
Yiyao Li ◽  
Jiangwei Cao ◽  
Shunfan Di ◽  
Wang Zhao ◽  
...  

2021 ◽  
Vol 5 (3) ◽  
pp. p39
Author(s):  
Chen Jinming

Environment perception is the basis of unmanned driving and obstacle detection is an important research area of environment perception technology. In order to quickly and accurately identify the obstacles in the direction of vehicle travel and obtain their location information, combined with the PCL (Point Cloud Library) function module, this paper designed a euclidean distance based Point Cloud clustering obstacle detection algorithm. Environmental information was obtained by 3D lidar, and ROI extraction, voxel filtering sampling, outlier point filtering, ground point cloud segmentation, Euclide clustering and other processing were carried out to achieve a complete PCL based 3D point cloud obstacle detection method. The experimental results show that the vehicle can effectively identify the obstacles in the area and obtain their location information.


2021 ◽  
Vol 1910 (1) ◽  
pp. 012002
Author(s):  
Chao He ◽  
Jiayuan Gong ◽  
Yahui Yang ◽  
Dong Bi ◽  
Jianpin Lan ◽  
...  

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