A Novel 3D LiDAR SLAM Based on Directed Geometry Point and Sparse Frame

doi:10.1109/LRA.2020.3043200

	A Novel 3D LiDAR SLAM Based on Directed Geometry Point and Sparse Frame
	Liang, Shuang1,2 ; Cao, Zhiqiang1,2 ; Wang, Chengpeng1,2 ; Yu, Junzhi1,3
发表期刊	IEEE ROBOTICS AND AUTOMATION LETTERS
ISSN	2377-3766
	2021-04-01
卷号	6 期号:2 页码:374-381
通讯作者	Cao, Zhiqiang(zhiqiang.cao@ia.ac.cn)
摘要	Simultaneous localization and mapping is an indispensable yet challenging direction for mobile robots. Attracted by 3D LiDAR with accurate depth information and robustness to illumination variations, many 3D LiDAR SLAM methods based on scan-to-map matching have been developed. However, there is a critical issue of existing approaches, where a large and dense map is generally required to achieve satisfactory localization accuracy, leading to low efficiency of scan-to-map matching. To solve this problem, in this letter, we propose a novel 3D LiDAR SLAM based on directed geometry point (DGP) and sparse frame. The former is used to provide a sparse distribution of points in the spatial dimension and the latter gives rise to a sparse distribution of frames in the temporal sequence. The sparsity of points and frames impove the efficiency of 3D LiDAR SLAM, and the strict data association based on directed geometric points also brings in good accuracy of pose estimation. To compensate the accuracy loss of the localization and mapping caused by frame sparsity, point propagation is proposed to improve the quality of directed geometric points in the map and the accuracy of scan-to-map matching. Also, loop detection and pose graph optimization are conducted for global consistency. The experimental results demonstrate the effectiveness of the proposed method in terms of accuracy and efficiency.
关键词	3D LiDAR SLAM directed geometric point sparse frame point propagation
DOI	10.1109/LRA.2020.3043200
关键词[WOS]	REGISTRATION
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[62073322] ; National Natural Science Foundation of China[61633020] ; National Natural Science Foundation of China[61633017] ; National Natural Science Foundation of China[61836015]
项目资助者	National Natural Science Foundation of China
WOS研究方向	Robotics
WOS类目	Robotics
WOS记录号	WOS:000602951000008
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
七大方向——子方向分类	机器人感知与决策
引用统计	被引频次：14[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/42808
专题	复杂系统认知与决策实验室_先进机器人
通讯作者	Cao, Zhiqiang
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Peking Univ, Coll Engn, BIC ESAT,Dept Mech & Engn Sci, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Liang, Shuang,Cao, Zhiqiang,Wang, Chengpeng,et al. A Novel 3D LiDAR SLAM Based on Directed Geometry Point and Sparse Frame[J]. IEEE ROBOTICS AND AUTOMATION LETTERS,2021,6(2):374-381.
APA	Liang, Shuang,Cao, Zhiqiang,Wang, Chengpeng,&Yu, Junzhi.(2021).A Novel 3D LiDAR SLAM Based on Directed Geometry Point and Sparse Frame.IEEE ROBOTICS AND AUTOMATION LETTERS,6(2),374-381.
MLA	Liang, Shuang,et al."A Novel 3D LiDAR SLAM Based on Directed Geometry Point and Sparse Frame".IEEE ROBOTICS AND AUTOMATION LETTERS 6.2(2021):374-381.