Service robot localization using improved particle filter

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Recently, Particle filter becomes the most popular approach in mobile robot localization and has been applied with great success to a variety of state estimation problems. In this paper, the particle filter is applied in position tracking and global localization. Moreover, the posterior distribution of robot pose in global localization is usually multimodal due to the symmetry of the environment and ambiguous detected features. Considering these characteristics, we proposed the cluster particle filter to improve the global localization robustness and accuracy. Experiment results show the effectiveness and robustness of our approach in our service robot ApriAlpha™ Platform.

Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Automation and Logistics, ICAL 2008
Pages2454-2459
Number of pages6
DOIs
Publication statusPublished - 2008
Externally publishedYes
EventIEEE International Conference on Automation and Logistics, ICAL 2008 - Qingdao
Duration: 2008 Sep 12008 Sep 3

Other

OtherIEEE International Conference on Automation and Logistics, ICAL 2008
CityQingdao
Period08/9/108/9/3

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Keywords

  • Cluster particle filter
  • Global localization
  • Particle filter
  • Service robot

ASJC Scopus subject areas

  • Artificial Intelligence
  • Hardware and Architecture
  • Control and Systems Engineering

Cite this

Cen, G., Matsuhira, N., Hirokawa, J., Ogawa, H., & Hagiwara, I. (2008). Service robot localization using improved particle filter. In Proceedings of the IEEE International Conference on Automation and Logistics, ICAL 2008 (pp. 2454-2459). [4636580] https://doi.org/10.1109/ICAL.2008.4636580