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Runtime reduction in optimal multi-query sampling-based motion planning

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dc.contributor.authorKhaksar W.en_US
dc.contributor.authorSahari K.S.B.M.en_US
dc.contributor.authorIsmail F.B.en_US
dc.contributor.authorYousefi M.en_US
dc.contributor.authorAli M.A.en_US
dc.contributor.authorid54960984900en_US
dc.contributor.authorid57218170038en_US
dc.contributor.authorid58027086700en_US
dc.contributor.authorid53985756300en_US
dc.contributor.authorid57214142487en_US
dc.date.accessioned2023-05-29T05:59:45Z
dc.date.available2023-05-29T05:59:45Z
dc.date.issued2015
dc.descriptionAlgorithms; Dispersions; Manufacture; Query processing; Robotics; High-dimensional; Low dispersions; Optimal solutions; Path length; Planning tasks; Sampling-based; Sampling-based algorithms; Sampling-based motion planning; Motion planningen_US
dc.description.abstractSampling-based motion planning algorithms have been successfully applied to various types of high-dimensional planning tasks. Recently an extension of PRM algorithm called PRM? planner has been proposed which guarantees asymptotic optimal solutions in terms of path length. However, the high runtime of sampling-based algorithms is still a serious disadvantage. In this paper, a new extension of PRM planner is proposed which incorporates the variable neighborhood radius feature of PRM? and the sampling radius of low-dispersion sampling in order to improve the cost of the generated solutions in terms of path length and runtime. The performance of the proposed algorithm is tested in different planning environments. Furthermore, the proposed planner is compared to the original PRM and the PRM? approaches and shows significant improvement. � 2014 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7295861
dc.identifier.doi10.1109/ROMA.2014.7295861
dc.identifier.epage56
dc.identifier.scopus2-s2.0-84959465777
dc.identifier.spage52
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84959465777&doi=10.1109%2fROMA.2014.7295861&partnerID=40&md5=fb80cb70f2066f99f3db777c247034ed
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22235
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2014 IEEE International Symposium on Robotics and Manufacturing Automation, IEEE-ROMA2014
dc.titleRuntime reduction in optimal multi-query sampling-based motion planningen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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