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Enhanced ground segmentation method for Lidar point clouds in human-centric autonomous robot systems
Chu,Phuong Minh1; Cho,Seoungjae1; Park,Jisun1; Fong,Simon2; Cho,Kyungeun1
2019-12-01
Source PublicationHuman-centric Computing and Information Sciences
Volume9Issue:1
AbstractGround segmentation is an important step for any autonomous and remote-controlled systems. After separating ground and nonground parts, many works such as object tracking and 3D reconstruction can be performed. 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 this 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, the point cloud in each obtained frame is divided 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 the proposed ground segment method. For flat and sloping terrains, the accuracy is over than 90%. Besides, the quality of the proposed method is also over than 80% for bumpy terrains. On the other hand, the speed is 145 frames per second. Therefore, in both simple and complex terrains, we gained good results and real-time performance.
KeywordAutonomous robot Ground segmentation Human-centric Internet of things Point cloud
DOI10.1186/s13673-019-0178-5
URLView the original
Language英语
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Cited Times [WOS]:7   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Corresponding AuthorCho,Kyungeun
Affiliation1.Department of Multimedia Engineering,Dongguk University-Seoul,Seoul,30 Pildong-ro 1-gil, Jung-gu,04620,South Korea
2.Department of Computer and Information Science,University of Macau,Macau,3000,China
Recommended Citation
GB/T 7714
Chu,Phuong Minh,Cho,Seoungjae,Park,Jisun,et al. Enhanced ground segmentation method for Lidar point clouds in human-centric autonomous robot systems[J]. Human-centric Computing and Information Sciences,2019,9(1).
APA Chu,Phuong Minh,Cho,Seoungjae,Park,Jisun,Fong,Simon,&Cho,Kyungeun.(2019).Enhanced ground segmentation method for Lidar point clouds in human-centric autonomous robot systems.Human-centric Computing and Information Sciences,9(1).
MLA Chu,Phuong Minh,et al."Enhanced ground segmentation method for Lidar point clouds in human-centric autonomous robot systems".Human-centric Computing and Information Sciences 9.1(2019).
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