Paper Info
Title
A Study of Sensor-Fusion Mechanism for Mobile Robot Global Localization.
Abstract
Estimating the robot state within a known map is an essential problem for mobile robot; it is also referred to "localization". Even LiDAR-based localization is practical in many applications, it is difficult to achieve global localization with LiDAR only for its low-dimension feedback, especially in environments with repetitive geometric features. A sensor-fusion-based localization system is introduced in this paper, which has the capability of addressing the global localization problem. Both LiDAR and vision sensors are integrated, making use of the rich information introduced by vision sensor and the robustness from LiDAR. A hybrid grid-map is built for global localization, and a visual global descriptor is applied to speed up the localization convergence, combined with a pose refining pipeline for improving the localization accuracy. Also, a trigger mechanism is introduced to solve kidnapped problem and verify the relocalization result. The experiments under different conditions are designed to evaluate the performance of the proposed approach, as well as a comparison with the existing localization systems. According to the experimental results, our system is able to solve the global localization problem, and the sensor-fusion mechanism in our system has an improved performance.
Year
DOI
Venue
2019
10.1017/S0263574719000298
ROBOTICA
Keywords
DocType
Volume
Mobile robot,Global localization,Sensor fusion
Journal
37
Issue
ISSN
Citations 
11
0263-5747
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Yonggang Chen101.01
Weinan Chen2145.72
lei zhu32523.09
Zerong Su400.34
Xuefeng Zhou53712.04
Yisheng Guan613745.41
Guanfeng Liu712.65