Utilization of Tabu search heuristic rules in sampling-based motion planning

Path planning in unknown environments is one of the most challenging research areas in robotics. In this class of path planning, the robot acquires the information from its sensory system. Sampling-based path planning is one of the famous approaches with low memory and computational requirements tha...

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Main Authors: Khaksar W., Hong T.S., Sahari K.S.M., Khaksar M.
Other Authors: 54960984900
Format: Conference Paper
Published: American Institute of Physics Inc. 2023
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spelling my.uniten.dspace-223382023-05-29T14:00:19Z Utilization of Tabu search heuristic rules in sampling-based motion planning Khaksar W. Hong T.S. Sahari K.S.M. Khaksar M. 54960984900 8231495000 57218170038 55350135000 Path planning in unknown environments is one of the most challenging research areas in robotics. In this class of path planning, the robot acquires the information from its sensory system. Sampling-based path planning is one of the famous approaches with low memory and computational requirements that has been studied by many researchers during the past few decades. We propose a sampling-based algorithm for path planning in unknown environments using Tabu search. The Tabu search component of the proposed method guides the sampling to find the samples in the most promising areas and makes the sampling procedure more intelligent. The simulation results show the efficient performance of the proposed approach in different types of environments. We also compare the performance of the algorithm with some of the well-known path planning approaches, including Bug1, Bug2, PRM, RRT and the Visibility Graph. The comparison results support the claim of superiority of the proposed algorithm. � 2015 AIP Publishing LLC. Final 2023-05-29T06:00:18Z 2023-05-29T06:00:18Z 2015 Conference Paper 10.1063/1.4915877 2-s2.0-85006208440 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006208440&doi=10.1063%2f1.4915877&partnerID=40&md5=2c42c8fcbd3b99489fac89b1cd4d987c https://irepository.uniten.edu.my/handle/123456789/22338 1660 90033 American Institute of Physics Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Path planning in unknown environments is one of the most challenging research areas in robotics. In this class of path planning, the robot acquires the information from its sensory system. Sampling-based path planning is one of the famous approaches with low memory and computational requirements that has been studied by many researchers during the past few decades. We propose a sampling-based algorithm for path planning in unknown environments using Tabu search. The Tabu search component of the proposed method guides the sampling to find the samples in the most promising areas and makes the sampling procedure more intelligent. The simulation results show the efficient performance of the proposed approach in different types of environments. We also compare the performance of the algorithm with some of the well-known path planning approaches, including Bug1, Bug2, PRM, RRT and the Visibility Graph. The comparison results support the claim of superiority of the proposed algorithm. � 2015 AIP Publishing LLC.
author2 54960984900
author_facet 54960984900
Khaksar W.
Hong T.S.
Sahari K.S.M.
Khaksar M.
format Conference Paper
author Khaksar W.
Hong T.S.
Sahari K.S.M.
Khaksar M.
spellingShingle Khaksar W.
Hong T.S.
Sahari K.S.M.
Khaksar M.
Utilization of Tabu search heuristic rules in sampling-based motion planning
author_sort Khaksar W.
title Utilization of Tabu search heuristic rules in sampling-based motion planning
title_short Utilization of Tabu search heuristic rules in sampling-based motion planning
title_full Utilization of Tabu search heuristic rules in sampling-based motion planning
title_fullStr Utilization of Tabu search heuristic rules in sampling-based motion planning
title_full_unstemmed Utilization of Tabu search heuristic rules in sampling-based motion planning
title_sort utilization of tabu search heuristic rules in sampling-based motion planning
publisher American Institute of Physics Inc.
publishDate 2023
_version_ 1806428495720480768
score 13.214268