A Novel Approach for Lidar-Based Robot Localization in a Scale-Drifted Map Constructed Using Monocular SLAM

Wang, Su; Kobayashi, Yukinori; Ravankar, Ankit A.; Ravankar, Abhijeet; Emaru, Takanori

A Novel Approach for Lidar-Based Robot Localization in a Scale-Drifted Map Constructed Using Monocular SLAM

Wang, Su; Kobayashi, Yukinori; Ravankar, Ankit A. et al.

Sensors, 2019, 19(10), 2230

Permalink : https://hdl.handle.net/2115/74993

このアイテムのアクセス数:720件（2026-08-09 20:30 集計）

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論文情報

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アクセス権	open access
URI	https://hdl.handle.net/2115/74993
タイトル	A Novel Approach for Lidar-Based Robot Localization in a Scale-Drifted Map Constructed Using Monocular SLAM
著者	Wang, Su ; Kobayashi, Yukinori ; Ravankar, Ankit A. ; Ravankar, Abhijeet ; Emaru, Takanori
著者名 Wang, Su
e-Rad_Researcher 10186778 著者名 Kobayashi, Yukinori
著者名 Ravankar, Ankit A.
著者名 Ravankar, Abhijeet
e-Rad_Researcher 30440952 著者名 Emaru, Takanori
言語	英語
キーワード	monocular SLAM
	localization
	scale drift
	state estimation
	heterogeneous robot system
発行日	2019-05-02
出版者	MDPI
収録物名	Sensors
巻(号)	19(10)
ページ	2230
抄録	Scale ambiguity and drift are inherent drawbacks of a pure-visual monocular simultaneous localization and mapping (SLAM) system. This problem could be a crucial challenge for other robots with range sensors to perform localization in a map previously built by a monocular camera. In this paper, a metrically inconsistent priori map is made by the monocular SLAM that is subsequently used to perform localization on another robot only using a laser range finder (LRF). To tackle the problem of the metric inconsistency, this paper proposes a 2D-LRF-based localization algorithm which allows the robot to locate itself and resolve the scale of the local map simultaneously. To align the data from 2D LRF to the map, 2D structures are extracted from the 3D point cloud map obtained by the visual SLAM process. Next, a modified Monte Carlo localization (MCL) approach is proposed to estimate the robot's state which is composed of both the robot's pose and map's relative scale. Finally, the effectiveness of the proposed system is demonstrated in the experiments on a public benchmark dataset as well as in a real-world scenario. The experimental results indicate that the proposed method is able to globally localize the robot in real-time. Additionally, even in a badly drifted map, the successful localization can also be achieved.
資源タイプ	学術雑誌論文
出版タイプ	Version of Record
権利情報	Creative Commons Attribution 4.0 International
PISSN	1424-8220
関連情報 (isIdenticalTo)	出版社版DOI https://doi.org/10.3390/s19102230