Improved Monte Carlo Localization with robust orientation estimation for mobile robots

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

6 Citations (Scopus)

Abstract

this paper proposes an improved Monte Carlo Localization algorithm with robust orientation estimation (IMCLROE) by incorporating an orientation estimate and weight calculation mechanism to determine an optimal orientation for particles and a tournament selection to reduce the number of particles for position tracking. Based on previously established sensory information, the proposed IMCLROE can improve the computational efficiency. Localization accuracy and localization failure rate are also significantly improved during position tracking while maintaining a minimal population of particles. Experimental results have confirmed the effectiveness of the proposed approach.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
Pages3651-3656
Number of pages6
DOIs
Publication statusPublished - 2013 Dec 1
Event2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 - Manchester, United Kingdom
Duration: 2013 Oct 132013 Oct 16

Other

Other2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
CountryUnited Kingdom
CityManchester
Period13/10/1313/10/16

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Keywords

  • Monte Carlo Localization
  • Orientation estimation
  • Particle filter
  • Position tracking
  • Robot localization

ASJC Scopus subject areas

  • Human-Computer Interaction

Cite this

Hsu, C-C. J., Kuo, C. J., & Kao, W-C. (2013). Improved Monte Carlo Localization with robust orientation estimation for mobile robots. In Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 (pp. 3651-3656). [6722375] https://doi.org/10.1109/SMC.2013.622