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

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dc.contributor.authorKhaksar W.en_US
dc.contributor.authorHong T.S.en_US
dc.contributor.authorSahari K.S.M.en_US
dc.contributor.authorKhaksar M.en_US
dc.contributor.authorid54960984900en_US
dc.contributor.authorid8231495000en_US
dc.contributor.authorid57218170038en_US
dc.contributor.authorid55350135000en_US
dc.date.accessioned2023-05-29T06:00:18Z
dc.date.available2023-05-29T06:00:18Z
dc.date.issued2015
dc.description.abstractPath 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.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo90033
dc.identifier.doi10.1063/1.4915877
dc.identifier.scopus2-s2.0-85006208440
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85006208440&doi=10.1063%2f1.4915877&partnerID=40&md5=2c42c8fcbd3b99489fac89b1cd4d987c
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22338
dc.identifier.volume1660
dc.publisherAmerican Institute of Physics Inc.en_US
dc.sourceScopus
dc.sourcetitleAIP Conference Proceedings
dc.titleUtilization of Tabu search heuristic rules in sampling-based motion planningen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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