Mobile robot global localization using particle filters

Guanghui Cen, Nobuto Matsuhira, Junko Hirokawa, Hideki Ogawa, Ichiro Hagiwara

研究成果: Conference contribution

16 被引用数 (Scopus)

抄録

Mobile robot global localization is the problem of determining a robot's pose in an environment by using sensor data, when the initial position is unknown. Particle filter based Probabilistic algorithm called Monte Carlo Localization is the current popular approach to solve the robot localization problem. In this paper we introduce the multi-sensor based Monte Carlo Localization (MCL) method which represents a robot's belief by a set of weighted samples and use the Laser Range Finder (LRF) sensor to measurement update. We also proposed likelihood based particle filter to solve the kidnapped problem. The experiment results illustrate the efficiency and robustness of particle filter approach for our mobile robot.

本文言語English
ホスト出版物のタイトル2008 International Conference on Control, Automation and Systems, ICCAS 2008
ページ710-713
ページ数4
DOI
出版ステータスPublished - 2008
外部発表はい
イベント2008 International Conference on Control, Automation and Systems, ICCAS 2008 - Seoul, Korea, Republic of
継続期間: 2008 10月 142008 10月 17

出版物シリーズ

名前2008 International Conference on Control, Automation and Systems, ICCAS 2008

Conference

Conference2008 International Conference on Control, Automation and Systems, ICCAS 2008
国/地域Korea, Republic of
CitySeoul
Period08/10/1408/10/17

ASJC Scopus subject areas

  • 制御およびシステム工学

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