A sonar data based particle filtering localization method for mobile robot

Author

En Liu, Xian ; Ma, Bojun ; Qi, Ningning ; Zhang, Zhenxin ; Ren, Dongchun

Author_Institution

Dept. of Autom., Nankai Univ., Tianjin

fYear

2008

fDate

25-27 June 2008

Firstpage

3920

Lastpage

3924

Abstract

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.

Keywords

Bayes methods; Markov processes; mobile robots; particle filtering (numerical methods); position control; sonar; Bayesian filtering theory; Markov process; global localization method; mobile robot; particle filtering localization method; sonar data; Bayesian methods; Filtering algorithms; Information filtering; Information filters; Information systems; Intelligent control; Intelligent robots; Mobile robots; Robotics and automation; Sonar; Bayesian formula; localization for mobile robot; particle filter; sonar sensor;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on

Conference_Location

Chongqing

Print_ISBN

978-1-4244-2113-8

Electronic_ISBN

978-1-4244-2114-5

Type

conf

DOI

10.1109/WCICA.2008.4593555

Filename

4593555