Study on optimal velocity selection using velocity obstacle (OVVO) in dynamic and crowded environment

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dc.contributor.authorKim, Min-Geukko
dc.contributor.authorOh, Jun-Hoko
dc.date.accessioned2016-12-01T04:41:03Z-
dc.date.available2016-12-01T04:41:03Z-
dc.date.created2016-01-08-
dc.date.created2016-01-08-
dc.date.issued2016-12-
dc.identifier.citationAUTONOMOUS ROBOTS, v.40, no.8, pp.1459 - 1470-
dc.identifier.issn0929-5593-
dc.identifier.urihttp://hdl.handle.net/10203/214393-
dc.description.abstractThe velocity obstacle (VO) method is one of local path generation method considering a velocity of obstacles. By dividing an available velocity region into collision and collision-free area, a robot can avoid collisions using the VO. However, if there are numerous obstacles near a robot, the robot will have very few velocity candidates. In this paper, a method to choose an optimal velocity by introducing a cost function about safety of the velocity, and the cost function consists of a pass-time and a clearance. By latticizing available velocity map of a robot, each velocity can be evaluated from the cost function and a robot can select better velocity among collision-free velocity candidates. A performance of introduced method is compared to other VO method using simulation, and experiments are conducted to verify the results of simulation.-
dc.languageEnglish-
dc.publisherSPRINGER-
dc.subjectGRAPH-
dc.titleStudy on optimal velocity selection using velocity obstacle (OVVO) in dynamic and crowded environment-
dc.typeArticle-
dc.identifier.wosid000386705700006-
dc.identifier.scopusid2-s2.0-84949684533-
dc.type.rimsART-
dc.citation.volume40-
dc.citation.issue8-
dc.citation.beginningpage1459-
dc.citation.endingpage1470-
dc.citation.publicationnameAUTONOMOUS ROBOTS-
dc.identifier.doi10.1007/s10514-015-9520-6-
dc.contributor.localauthorOh, Jun-Ho-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorDynamic obstacle-
dc.subject.keywordAuthorMobile robot-
dc.subject.keywordAuthorVelocity obstacle-
dc.subject.keywordAuthorPass-time-
dc.subject.keywordAuthorOptimization-
dc.subject.keywordPlusAVOIDANCE-
dc.subject.keywordPlusGRAPH-
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