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A study on searching optimal path for robot using genetic algorithm
  • Park, So Young ;
  • Park, Pyoung Woo ;
  • Kim, Jung Min ;
  • Borm, Jin Hwan ;
  • Lee, Seok Won
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dc.contributor.authorPark, So Young-
dc.contributor.authorPark, Pyoung Woo-
dc.contributor.authorKim, Jung Min-
dc.contributor.authorBorm, Jin Hwan-
dc.contributor.authorLee, Seok Won-
dc.date.issued2018-12-01-
dc.identifier.urihttps://dspace.ajou.ac.kr/dev/handle/2018.oak/30494-
dc.description.abstractThis paper presents a search methodology for the optimal operational path of robots using a genetic algorithm. The work scheduled to be performed using a robot was characterized. Collision avoidance between the robot including the working tool and the target object was considered. In this study, we followed the general steps of data mining. We compared the time taken by the robot moving along the path created by our proposed methodology with the time taken for the robot along the path created by real humans. The results show that the path generated by this study was more efficient than that of humans.-
dc.language.isoeng-
dc.publisherKorean Society for Precision Engineeing-
dc.titleA study on searching optimal path for robot using genetic algorithm-
dc.typeArticle-
dc.citation.endPage1155-
dc.citation.startPage1147-
dc.citation.titleJournal of the Korean Society for Precision Engineering-
dc.citation.volume35-
dc.identifier.bibliographicCitationJournal of the Korean Society for Precision Engineering, Vol.35, pp.1147-1155-
dc.identifier.doi10.7736/kspe.2018.35.12.1147-
dc.identifier.scopusid2-s2.0-85057750145-
dc.identifier.urlhttp://journal.kspe.or.kr/archive/paper_file_download.kin?no=916-
dc.subject.keywordGenetic algorithm-
dc.subject.keywordIndustrial robot-
dc.subject.keywordOptimal path-
dc.subject.keywordPath searching-
dc.description.isoafalse-
dc.subject.subareaSafety, Risk, Reliability and Quality-
dc.subject.subareaMechanical Engineering-
dc.subject.subareaIndustrial and Manufacturing Engineering-
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