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Cited 9 time in webofscience Cited 19 time in scopus
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Advanced Fuzzy Potential Field Method for Mobile Robot Obstacle Avoidance

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dc.contributor.authorPark, Jong-Wook-
dc.contributor.authorKwak, Hwan-Joo-
dc.contributor.authorKang, Young-Chang-
dc.contributor.authorKim, Dong W.-
dc.date.available2020-02-28T06:43:40Z-
dc.date.created2020-02-06-
dc.date.issued2016-
dc.identifier.issn1687-5265-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/9716-
dc.description.abstractAn advanced fuzzy potential field method for mobile robot obstacle avoidance is proposed. The potential field method primarily deals with the repulsive forces surrounding obstacles, while fuzzy control logic focuses on fuzzy rules that handle linguistic variables and describe the knowledge of experts. The design of a fuzzy controller-advanced fuzzy potential field method (AFPFM)-that models and enhances the conventional potential field method is proposed and discussed. This study also examines the rule-explosion problem of conventional fuzzy logic and assesses the performance of our proposed AFPFM through simulations carried out using a mobile robot.-
dc.language영어-
dc.language.isoen-
dc.publisherHINDAWI LTD-
dc.relation.isPartOfCOMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE-
dc.subjectSYSTEMS-
dc.subjectDESIGN-
dc.titleAdvanced Fuzzy Potential Field Method for Mobile Robot Obstacle Avoidance-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.wosid000374418800001-
dc.identifier.doi10.1155/2016/6047906-
dc.identifier.bibliographicCitationCOMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE-
dc.identifier.scopusid2-s2.0-84971482849-
dc.citation.titleCOMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE-
dc.contributor.affiliatedAuthorKang, Young-Chang-
dc.type.docTypeArticle-
dc.subject.keywordPlusSYSTEMS-
dc.subject.keywordPlusDESIGN-
dc.relation.journalResearchAreaMathematical & Computational Biology-
dc.relation.journalResearchAreaNeurosciences & Neurology-
dc.relation.journalWebOfScienceCategoryMathematical & Computational Biology-
dc.relation.journalWebOfScienceCategoryNeurosciences-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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