New solutions to the premature convergence problem in Monte Carlo localization

Chiang Heng Chien, Chen Chien Hsu, Wei Yen Wang, Wen Chung Kao, Chiang Ju Chien

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

1 Citation (Scopus)

Abstract

In this paper, a new solution towards the premature convergence problem in Monte Carlo Localization for global localization under highly symmetrical environments is proposed. The algorithm employs a "standard direction" to allow particles to move so as to rearrange weights, providing better exploration as a result. Therefore, there are higher opportunities for particles to converge to the real robot pose and prevent premature convergence accordingly. Experiments have verified the proposed algorithm to be reliable and robust by offering notable improvements in the global localization performance.

Original languageEnglish
Title of host publication2016 IEEE 6th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2016
EditorsTom Wilson, Wolfgang Endemann, Hans L. Cycon, Dietmar Hepper, Jose Maria Flores-Arias
PublisherIEEE Computer Society
Pages83-84
Number of pages2
ISBN (Electronic)9781509020966
DOIs
Publication statusPublished - 2016 Oct 25
Event6th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2016 - Berlin, Germany
Duration: 2016 Sept 52016 Sept 7

Publication series

NameIEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
Volume2016-October
ISSN (Print)2166-6814
ISSN (Electronic)2166-6822

Other

Other6th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2016
Country/TerritoryGermany
CityBerlin
Period2016/09/052016/09/07

Keywords

  • Global Localization
  • Monte Carlo Localization
  • Premature Convergence

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Media Technology

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