A Point-Line VIO System With Novel Feature Hybrids and With Novel Line Predicting-Matching

doi:10.1109/LRA.2021.3113987

	A Point-Line VIO System With Novel Feature Hybrids and With Novel Line Predicting-Matching
	Wei, Hao 1,2; Tang, Fulin2 ; Xu, Zewen 1,2; Zhang, Chaofan 3; Wu, Yihong1,2
Source Publication	IEEE ROBOTICS AND AUTOMATION LETTERS
ISSN	2377-3766
	2021-10-01
Volume	6 Issue:4 Pages:8681-8688
Corresponding Author	Zhang, Chaofan(zcfan@aiofm.ac.cn) ; Wu, Yihong(yihong.wu@ia.ac.cn)
Abstract	Weak texture and motion blur are always challenging problems for visual-inertial odometry (VIO) systems. To improve accuracy of VIO systems in the challenging scenes, we propose a point-line-based VIO system with novel feature hybrids and with novel predicting-matching for long line track. Point-line features with shorter tracks are categorized into "MSCKF" features and with longer tracks into "SLAM" features. Especially, "SLAM" lines are added into the state vector to improve accuracy of the proposed system. Besides, to ensure the reliability and stability of detection and tracking of line features, we also propose a new "Predicting-Matching" line segment tracking method to increase the track lengths of line segments. Experimental results show that the proposed method outperforms the state-of-the-art methods of VINS-Mono [1], PL-VINS [2] and OpenVINS [3]) on both a public dataset and a collected dataset in terms of accuracy. The collected dataset is full of extremely weak textures and motion blurs. On this dataset, the proposed method also obtains better accuracy than ORB-SLAM3 [4].
Keyword	Simultaneous localization and mapping Feature extraction Three-dimensional displays Tracking Jacobian matrices Motion segmentation Cameras Visual-Inertial SLAM SLAM
DOI	10.1109/LRA.2021.3113987
WOS Keyword	ROBUST
Indexed By	SCI
Language	英语
Funding Project	National Natural Science Foundation of China[61836015] ; National Natural Science Foundation of China[62002359] ; Beijing Advanced Discipline Fund[115200S001]
Funding Organization	National Natural Science Foundation of China ; Beijing Advanced Discipline Fund
WOS Research Area	Robotics
WOS Subject	Robotics
WOS ID	WOS:000704109700008
Publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Sub direction classification	三维视觉
Citation statistics
Document Type	期刊论文
Identifier	http://ir.ia.ac.cn/handle/173211/45754
Collection	模式识别国家重点实验室_机器人视觉
Corresponding Author	Zhang, Chaofan; Wu, Yihong
Affiliation	1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100864, Peoples R China 3.Chinese Acad Sci, Hefei Inst Phys Sci, Anhui Inst Opt & Fine Mech, Hefei 230031, Peoples R China
First Author Affilication	Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author Affilication	Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation GB/T 7714	Wei, Hao,Tang, Fulin,Xu, Zewen,et al. A Point-Line VIO System With Novel Feature Hybrids and With Novel Line Predicting-Matching[J]. IEEE ROBOTICS AND AUTOMATION LETTERS,2021,6(4):8681-8688.
APA	Wei, Hao,Tang, Fulin,Xu, Zewen,Zhang, Chaofan,&Wu, Yihong.(2021).A Point-Line VIO System With Novel Feature Hybrids and With Novel Line Predicting-Matching.IEEE ROBOTICS AND AUTOMATION LETTERS,6(4),8681-8688.
MLA	Wei, Hao,et al."A Point-Line VIO System With Novel Feature Hybrids and With Novel Line Predicting-Matching".IEEE ROBOTICS AND AUTOMATION LETTERS 6.4(2021):8681-8688.

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