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공지사항
논문명 |
Enhanced Ground Segmentation Method for Lidar Point Clouds in Autonomous Robot Systems |
구분 |
국내발표 |
저자 |
Phuong Minh Chu, Seoungjae Cho, Jisun Park, Simon Fong, Kyungeun Cho |
국내/국외 |
|
학술회의명 |
The International Conference on Big data, IoT, and Cloud Computing |
개최국가 |
대한민국 |
주관기관 |
|
게재일 |
2018.08 |
In this paper, we propose an efficient method for segmenting the ground data of point clouds acquired from multi-channel Lidar sensors. The goal of our study is to completely separate ground points and nonground points in real time. The proposed method segments ground data efficiently and accurately in various environments such as flat terrain, undulating/rugged terrain, and mountainous terrain. First, we divide the point cloud in each obtained frame into small groups. We then focus on the vertical and horizontal directions separately, before processing both directions concurrently. Experiments were conducted, and the results showed the effectiveness of our ground segment method. In both simple and complex terrains, we gained the good results and real-time performance. |
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