Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping

An artificial intelligent grey wolf optimizer (GWO)-assisted resampling scheme is applied to the Rao-Blackwellized particle filter (RBPF) in the simultaneous localization and mapping (SLAM). By doing this, we can make the diversity of the particles resampling and then obtain a better localization ac...

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Autores principales:	Yong Dai, Ming Zhao
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Mechanical engineering and machinery TJ1-1570
Acceso en línea:	https://doaj.org/article/112e8fb2dfc740b592ba6a39dc9d4d54
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spelling	oai:doaj.org-article:112e8fb2dfc740b592ba6a39dc9d4d542021-11-08T02:35:20ZGrey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping1687-961910.1155/2021/4978984https://doaj.org/article/112e8fb2dfc740b592ba6a39dc9d4d542021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/4978984https://doaj.org/toc/1687-9619An artificial intelligent grey wolf optimizer (GWO)-assisted resampling scheme is applied to the Rao-Blackwellized particle filter (RBPF) in the simultaneous localization and mapping (SLAM). By doing this, we can make the diversity of the particles resampling and then obtain a better localization accuracy and fast convergence to realize indoor mobile robot SLAM. In addition, we propose an adaptive local data association (Range-SLAM) scheme to improve the computational efficiency for the algorithm of the nearest neighbor (NN) data association in the iteration of the RBPF prediction. Through the experiment and simulations, the proposed SLAM schemes have fast convergence, accuracy, and heuristics. Therefore, the improved RBPF and new data association schemes presented in this paper can provide a feasible method for the indoor mobile robot SLAM.Yong DaiMing ZhaoHindawi LimitedarticleMechanical engineering and machineryTJ1-1570ENJournal of Robotics, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Mechanical engineering and machinery TJ1-1570
spellingShingle	Mechanical engineering and machinery TJ1-1570 Yong Dai Ming Zhao Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping
description	An artificial intelligent grey wolf optimizer (GWO)-assisted resampling scheme is applied to the Rao-Blackwellized particle filter (RBPF) in the simultaneous localization and mapping (SLAM). By doing this, we can make the diversity of the particles resampling and then obtain a better localization accuracy and fast convergence to realize indoor mobile robot SLAM. In addition, we propose an adaptive local data association (Range-SLAM) scheme to improve the computational efficiency for the algorithm of the nearest neighbor (NN) data association in the iteration of the RBPF prediction. Through the experiment and simulations, the proposed SLAM schemes have fast convergence, accuracy, and heuristics. Therefore, the improved RBPF and new data association schemes presented in this paper can provide a feasible method for the indoor mobile robot SLAM.
format	article
author	Yong Dai Ming Zhao
author_facet	Yong Dai Ming Zhao
author_sort	Yong Dai
title	Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping
title_short	Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping
title_full	Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping
title_fullStr	Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping
title_full_unstemmed	Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping
title_sort	grey wolf resampling-based rao-blackwellized particle filter for mobile robot simultaneous localization and mapping
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/112e8fb2dfc740b592ba6a39dc9d4d54
work_keys_str_mv	AT yongdai greywolfresamplingbasedraoblackwellizedparticlefilterformobilerobotsimultaneouslocalizationandmapping AT mingzhao greywolfresamplingbasedraoblackwellizedparticlefilterformobilerobotsimultaneouslocalizationandmapping
_version_	1718443161760563200

Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping

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