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A Study of Sensor-Fusion Mechanism for Mobile Robot Global Localization

Published online by Cambridge University Press:  22 April 2019

Yonggang Chen ,
Weinan Chen Open the ORCID record for Weinan Chen [Opens in a new window] ,
Lei Zhu ,
Zerong Su ,
Xuefeng Zhou ,
Yisheng Guan  and
Guanfeng Liu
Yonggang Chen
Affiliation:
School of Electro-mechanical Engineering, Guangdong University of Technology, Guangzhou, China. E-mails: [email protected], [email protected] Department of Electro-mechanical Engineering, Dongguan Polytechnic, Dongguan, China. E-mail: [email protected]
Weinan Chen*
Affiliation:
School of Electro-mechanical Engineering, Guangdong University of Technology, Guangzhou, China. E-mails: [email protected], [email protected]
Lei Zhu
Affiliation:
School of Electro-mechanical Engineering, Guangdong University of Technology, Guangzhou, China. E-mails: [email protected], [email protected]
Zerong Su
Affiliation:
Guangdong Key Laboratory of Modern Control Technology, Guangdong Institute of Intelligent Manufacturing, Guangzhou, China. E-mails: [email protected], [email protected]
Xuefeng Zhou
Affiliation:
Guangdong Key Laboratory of Modern Control Technology, Guangdong Institute of Intelligent Manufacturing, Guangzhou, China. E-mails: [email protected], [email protected]
Yisheng Guan
Affiliation:
School of Electro-mechanical Engineering, Guangdong University of Technology, Guangzhou, China. E-mails: [email protected], [email protected]
Guanfeng Liu
Affiliation:
Guangdong Polytechnic Normal University, Guangzhou, China. E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

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.

Keywords

Mobile robotGlobal localizationSensor fusion
Type
Articles
Information
Robotica , Volume 37 , Issue 11 , November 2019 , pp. 1835 - 1849
Copyright
© Cambridge University Press 2019 

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Footnotes

The first two authors contributed equally to this work.

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