A lightweight localization strategy for lidar-guided autonomous robots with artificial landmarks

doi:10.3390/s21134479

CIOMP OpenIR

	A lightweight localization strategy for lidar-guided autonomous robots with artificial landmarks
	S. Wang; X. Chen; G. Ding; Y. Li; X. W; Z. Q; G. Y and S. Q
	2021
发表期刊	Sensors
ISSN	14248220
卷号	21 期号:13
摘要	This paper proposes and implements a lightweight, "real-time" localization system (SORLA) with artificial landmarks (reflectors), which only uses LiDAR data for the laser odometer compensation in the case of high-speed or sharp-turning. Theoretically, due to the feature-matching mechanism of the LiDAR, locations of multiple reflectors and the reflector layout are not limited by geometrical relation. A series of algorithms is implemented to find and track the features of the environment, such as the reflector localization method, the motion compensation technique, and the reflector matching optimization algorithm. The reflector extraction algorithm is used to identify the reflector candidates and estimates the precise center locations of the reflectors from 2D LiDAR data. The motion compensation algorithm predicts the potential velocity, location, and angle of the robot without odometer errors. Finally, the matching optimization algorithm searches the reflector combinations for the best matching score, which ensures that the correct reflector combination could be found during the high-speed movement and fast turning. All those mechanisms guarantee the algorithms precision and robustness in the high speed and noisy background. Our experimental results show that the SORLA algorithm has an average localization error of 6.45 mm at a speed of 0.4 m/s, and 9.87 mm at 4.2 m/s, and still works well with the angular velocity of 1.4 rad/s at a sharp turn. The recovery mechanism in the algorithm could handle the failure cases of reflector occlusion, and the long-term stability test of 72 h firmly proves the algorithms robustness. This work shows that the strategy used in the SORLA algorithm is feasible for industry-level navigation with high precision and a promising alternative solution for SLAM. 2021 by the authors. Licensee MDPI, Basel, Switzerland.
DOI	10.3390/s21134479
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收录类别	SCI ; EI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/65387
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	S. Wang,X. Chen,G. Ding,et al. A lightweight localization strategy for lidar-guided autonomous robots with artificial landmarks[J]. Sensors,2021,21(13).
APA	S. Wang.,X. Chen.,G. Ding.,Y. Li.,X. W.,...&G. Y and S. Q.(2021).A lightweight localization strategy for lidar-guided autonomous robots with artificial landmarks.Sensors,21(13).
MLA	S. Wang,et al."A lightweight localization strategy for lidar-guided autonomous robots with artificial landmarks".Sensors 21.13(2021).

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