An Algorithm for Road Boundary Extraction and Obstacle Detection Based on 3D Lidar

被引：0
|
作者：
Wang C. [1 ,2 ]
Kong B. [1 ,2 ]
Yang J. [1 ,2 ]
Wang Z. [2 ,3 ]
Zhu H. [2 ,3 ]
机构：
[1] Special Robot Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei
[2] Anhui Engineering Laboratory for Intelligent Driving Technology and Application, Hefei
[3] Research Center of Intelligent Vehicle Technology, Institute of Applied Technology, Hefei Institutes of Physical Science Chinese Academy of Sciences, Hefei
来源：
Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence | 2020年 / 33卷 / 04期
基金：
中国国家自然科学基金;
关键词：
3D Lidar; Obstacle Detection; Point Cloud Processing; Road Boundary; Unmanned Vehicle;
D O I：
10.16451/j.cnki.issn1003-6059.202004008
中图分类号：
学科分类号：
摘要：
To extract relevant road information quickly and effectively for intelligent vehicles in various road environments, an algorithm for real-time road boundary extraction and obstacle detection based on three-dimensional (3D) lidar is proposed. Firstly, 3D lidar point cloud data is rasterized and filtered, and the single beam laser point cloud spatial segmentation method is employed for spatial analysis to obtain the point cloud smoothness characteristic image. Then, the adaptive direction search algorithm is adopted to obtain the road boundary feature points and perform cluster analysis and curve fitting. Finally, the point cloud in the passable area is clustered and segmented under the road boundary constraint to obtain the obstacle position information. Experiments show that the proposed algorithm extracts road boundary and obstacle location information accurately in real time, and it meets the requirements of environment modeling and path planning for intelligent vehicle. © 2020, Science Press. All right reserved.
引用
收藏
页码：353 / 362
页数：9
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