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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Main Authors: Yong Dai, Ming Zhao
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Journal of Robotics
Online Access:http://dx.doi.org/10.1155/2021/4978984
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author Yong Dai
Ming Zhao
author_facet Yong Dai
Ming Zhao
author_sort Yong Dai
collection DOAJ
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.
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institution Kabale University
issn 1687-9619
language English
publishDate 2021-01-01
publisher Wiley
record_format Article
series Journal of Robotics
spelling doaj-art-112e8fb2dfc740b592ba6a39dc9d4d542025-08-20T03:55:45ZengWileyJournal of Robotics1687-96192021-01-01202110.1155/2021/49789844978984Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and MappingYong Dai0Ming Zhao1School of Automation and Electrical EngineeringSchool of Applied TechnologyAn 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.http://dx.doi.org/10.1155/2021/4978984
spellingShingle Yong Dai
Ming Zhao
Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping
Journal of Robotics
title 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_short 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
url http://dx.doi.org/10.1155/2021/4978984
work_keys_str_mv AT yongdai greywolfresamplingbasedraoblackwellizedparticlefilterformobilerobotsimultaneouslocalizationandmapping
AT mingzhao greywolfresamplingbasedraoblackwellizedparticlefilterformobilerobotsimultaneouslocalizationandmapping