A sonar data based particle filtering localization method for mobile robot

A global localization method is proposed for mobile robot. This algorithm is based on Bayesian filtering theory and Markov process. A set of particles is utilized to describe the distribution of robot localization. The set is updated according to the map information and sonar data step by step. In t...

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Bibliographic Details
Published in2008 7th World Congress on Intelligent Control and Automation pp. 3920 - 3924
Main Authors Xian'en Liu, Bojun Ma, Ningning Qi, Zhenxin Zhang, Dongchun Ren
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2008
Subjects
Automation
Bayesian formula
Filtering
localization for mobile robot
Mobile robots
particle filter
Particle filters
Robot localization
Robots
Sonar
sonar sensor
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Summary:A global localization method is proposed for mobile robot. This algorithm is based on Bayesian filtering theory and Markov process. A set of particles is utilized to describe the distribution of robot localization. The set is updated according to the map information and sonar data step by step. In this way the particles converge to the true localization rapidly. In this paper, the map is recorded as set of sections of line, which takes little storage space and benefit calculation. Simulation results show the effectiveness of this algorithm.
ISBN:1424421136
9781424421138
DOI:10.1109/WCICA.2008.4593555