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Map-based localization for mobile robots in high-occluded and dynamic environments

Yong Wang (Department of Automation, Shanghai Jiao Tong University, Shanghai, China, Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China and State Key Laboratory of Robotics and System, Harbin Institute of Technology (HIT), Harbin, China)
Weidong Chen (Department of Automation, Shanghai Jiao Tong University, Shanghai, China, Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China and State Key Laboratory of Robotics and System, Harbin Institute of Technology (HIT), Harbin, China)
Jingchuan Wang (Department of Automation, Shanghai Jiao Tong University, Shanghai, China, Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China and State Key Laboratory of Robotics and System, Harbin Institute of Technology (HIT), Harbin, China)

Industrial Robot

ISSN: 0143-991x

Article publication date: 13 May 2014

364

Abstract

Purpose

The purpose of this paper is to propose a localizability-based particle filtering localization algorithm for mobile robots to maintain localization accuracy in the high-occluded and dynamic environments with moving people.

Design/methodology/approach

First, the localizability of mobile robots is defined to evaluate the influences of both the dynamic obstacles and prior-map on localization. Second, based on the classical two-sensor track fusion algorithm, the odometer-based proposal distribution function (PDF) is corrected, taking account of the localizability. Then, the corrected PDF is introduced into the classical PF with “roulette” re-sampling. Finally, the robot pose is estimated according to all the particles.

Findings

The experimental results show that, first, it is necessary to consider the influence of the prior-map during the localization in the high-occluded and dynamic environments. Second, the proposed algorithm can maintain an accurate and robust robot pose in the high-occluded and dynamic environments. Third, its real timing is acceptable.

Research limitations/implications

When the odometer error and occlusion caused by the dynamic obstacles are both serious, the proposed algorithm also has a probability evolving into the kidnap problem. But fortunately, such serious situations are not common in practice.

Practical implications

To check the ability of real application, we have implemented the proposed algorithm in the campus cafeteria and metro station using an intelligent wheelchair. To better help the elderly and disabled people during their daily lives, the proposed algorithm will be tested in a social welfare home in the future.

Original/value

The localizability of mobile robots is defined to evaluate the influences of both the dynamic obstacles and prior-map on localization. Based on the localizability, the odometer-based PDF is corrected properly.

Keywords

Acknowledgements

This study is partly supported by the National High Technology Research and Development Program of China (2012AA041403), Natural Science Foundation of China (60934006, 61175088), Research Fund for the Doctoral Program of Higher Education (20100073110018) and State Key Laboratory of Robotics and System (HIT) (SKLRS2011ZD01).

Citation

Wang, Y., Chen, W. and Wang, J. (2014), "Map-based localization for mobile robots in high-occluded and dynamic environments", Industrial Robot, Vol. 41 No. 3, pp. 241-252. https://doi.org/10.1108/IR-06-2013-371

Publisher

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Emerald Group Publishing Limited

Copyright © 2014, Emerald Group Publishing Limited

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