Paper Info
Title
MSTSL: Multi-Sensor Based Two-Step Localization in Geometrically Symmetric Environments
Abstract
Symmetric environment is one of the most intractable and challenging scenarios for mobile robots to accomplish global localization tasks, due to the highly similar geometrical structures and insufficient distinctive features. Existing localization solutions in such scenarios either depend on pre-deployed infrastructures which are expensive, inflexible, and hard to maintain; or rely on single sensor-based methods whose initialization module is incapable to provide enough unique information. Thus, this paper proposes a novel Multi-Sensor based Two-Step Localization framework named MSTSL, which addresses the problem of mobile robot global localization in geometrically symmetric environments by utilizing the measured magnetic field, 2-D LiDAR, and wheel odometry information. The proposed system mainly consists of two steps: 1) Magnetic Field-based Initialization, and 2) LiDAR-based Localization. Based on the pre-built magnetic field database, multiple initial hypotheses poses can firstly be determined by the proposed two-stage initialization algorithm. Then, utilizing the obtained multiple initial hypotheses, the robot can be localized more accurately by LiDAR-based localization. Extensive experiments demonstrate the practical utility and accuracy of the proposed system over the alternative approaches in real-world scenarios.
Year
DOI
Venue
2021
10.1109/ICRA48506.2021.9561471
2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021)
DocType
Volume
Issue
Conference
2021
1
ISSN
Citations 
PageRank 
1050-4729
0
0.34
References 
Authors
8
6
Name
Order
Citations
PageRank
Wu Zhenyu113.39
Yufeng Yue214.40
Mingxing Wen325.44
Jun Zhang41102188.11
Guohao Peng522.06
Danwei Wang61529175.13