Global localization of Monte Carlo localization based on multi-objective particle swarm optimization

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

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

5 Citations (Scopus)

Abstract

Premature convergence often happens when a Monte Carlo localization (MCL) algorithm tries to localize a robot under highly symmetrical environments. In this paper, we propose a novel method of solving such problem for global localization by incorporating a multi-objective evolutionary approach to resample particles with two objectives, including particle weights and population distribution. By employing a multi-objective particle swarm optimization (MOPSO), our approach is capable of enhancing the exploration ability to improve population diversity while maintaining convergence quality to successfully localize the global optima. Simulation results have confirmed that localization performance using the proposed approach is significantly improved.

Original languageEnglish
Title of host publication2016 IEEE 6th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2016
PublisherIEEE Computer Society
Pages96-97
Number of pages2
Volume2016-October
ISBN (Electronic)9781509020966
DOIs
Publication statusPublished - 2016 Oct 25
Event6th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2016 - Berlin, Germany
Duration: 2016 Sep 52016 Sep 7

Other

Other6th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2016
CountryGermany
CityBerlin
Period16/9/516/9/7

Fingerprint

Population distribution
Particle swarm optimization (PSO)
Robots

Keywords

  • Global Localization
  • Monte Carlo localization
  • Multi-Objective Particle Swarm Optimization
  • Premature Convergence

ASJC Scopus subject areas

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

Cite this

Chien, C. H., Hsu, C. C., Wang, W. Y., Kao, W. C., & Chien, C. J. (2016). Global localization of Monte Carlo localization based on multi-objective particle swarm optimization. In 2016 IEEE 6th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2016 (Vol. 2016-October, pp. 96-97). [7684728] IEEE Computer Society. https://doi.org/10.1109/ICCE-Berlin.2016.7684728

Global localization of Monte Carlo localization based on multi-objective particle swarm optimization. / Chien, Chiang Heng; Hsu, Chen Chien; Wang, Wei Yen; Kao, Wen Chung; Chien, Chiang Ju.

2016 IEEE 6th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2016. Vol. 2016-October IEEE Computer Society, 2016. p. 96-97 7684728.

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

Chien, CH, Hsu, CC, Wang, WY, Kao, WC & Chien, CJ 2016, Global localization of Monte Carlo localization based on multi-objective particle swarm optimization. in 2016 IEEE 6th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2016. vol. 2016-October, 7684728, IEEE Computer Society, pp. 96-97, 6th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2016, Berlin, Germany, 16/9/5. https://doi.org/10.1109/ICCE-Berlin.2016.7684728
Chien CH, Hsu CC, Wang WY, Kao WC, Chien CJ. Global localization of Monte Carlo localization based on multi-objective particle swarm optimization. In 2016 IEEE 6th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2016. Vol. 2016-October. IEEE Computer Society. 2016. p. 96-97. 7684728 https://doi.org/10.1109/ICCE-Berlin.2016.7684728
Chien, Chiang Heng ; Hsu, Chen Chien ; Wang, Wei Yen ; Kao, Wen Chung ; Chien, Chiang Ju. / Global localization of Monte Carlo localization based on multi-objective particle swarm optimization. 2016 IEEE 6th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2016. Vol. 2016-October IEEE Computer Society, 2016. pp. 96-97
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