운동계획을 위한 입자 군집 최적화를 이용한시범에 의한 학습의 적응성 향상Adaptability Improvement of Learning from Demonstration with Particle Swarm Optimization for Motion Planning

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dc.contributor.author김정중ko
dc.contributor.author이주장ko
dc.date.accessioned2019-03-08T15:59:10Z-
dc.date.available2019-03-08T15:59:10Z-
dc.date.created2017-04-04-
dc.date.issued2016-12-
dc.identifier.citation한국산업융합학회논문집, v.19, no.4, pp.167 - 175-
dc.identifier.issn1226-833x-
dc.identifier.urihttp://hdl.handle.net/10203/251131-
dc.description.abstractWe present a method for improving adaptability of Learning from Demonstration (LfD) strategy by combining the LfD and Particle Swarm Optimization (PSO). A trajectory generated from an LfD is modified with PSO by minimizing a fitness function that considers constraints. Finally, the final trajectory is suitable for a task and adapted for constraints. The effectiveness of the method is shown with a target reaching task with a manipulator in three-dimensional space.-
dc.languageKorean-
dc.publisher한국산업융합학회-
dc.subjectMotion planning-
dc.subjectParticle swarm optimization-
dc.subjectLearning-
dc.subjectManipulator-
dc.title운동계획을 위한 입자 군집 최적화를 이용한시범에 의한 학습의 적응성 향상-
dc.title.alternativeAdaptability Improvement of Learning from Demonstration with Particle Swarm Optimization for Motion Planning-
dc.typeArticle-
dc.type.rimsART-
dc.citation.volume19-
dc.citation.issue4-
dc.citation.beginningpage167-
dc.citation.endingpage175-
dc.citation.publicationname한국산업융합학회논문집-
dc.identifier.kciidART002187576-
dc.contributor.localauthor이주장-
dc.contributor.nonIdAuthor김정중-
dc.description.isOpenAccessN-
dc.subject.keywordAuthorMotion planning-
dc.subject.keywordAuthorParticle swarm optimization-
dc.subject.keywordAuthorLearning-
dc.subject.keywordAuthorManipulator-
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EE-Journal Papers(저널논문)
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