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Convolution-Based Trajectory Generation Methods Using Physical System Limits

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dc.contributor.authorLee, Geon-
dc.contributor.authorKim, Jinhyun-
dc.contributor.authorChoi, Youngjin-
dc.date.accessioned2021-06-23T04:22:53Z-
dc.date.available2021-06-23T04:22:53Z-
dc.date.issued2013-01-
dc.identifier.issn0022-0434-
dc.identifier.issn1528-9028-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/29240-
dc.description.abstractThis paper proposes two novel convolution-based trajectory generation methods using physical system limits such as maximum velocity, maximum acceleration, and maximum jerk. Convolution is a mathematical operation on two functions of an input function and a convoluted function, producing an output function that is typically viewed as a modified version of input function. Time duration parameters of the convoluted functions with a unit area are determined from the given physical system limits. The convolution-based trajectory generation methods to be proposed in this paper have three advantages; first, a continuously differentiable trajectory is simply obtained by applying successive convolution operations; second, a resultant trajectory is always generated satisfying the given physical system limits; third, the suggested methods have low computational burden thanks to recursive form of convolution operation. The suggested methods consider both zero and nonzero initial/terminal conditions. Finally, the effectiveness of the suggested methods is shown through numerical simulations. [DOI: 10.1115/1.4007551]-
dc.format.extent8-
dc.language영어-
dc.language.isoENG-
dc.publisherASME-
dc.titleConvolution-Based Trajectory Generation Methods Using Physical System Limits-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1115/1.4007551-
dc.identifier.scopusid2-s2.0-84872835314-
dc.identifier.wosid000313672000001-
dc.identifier.bibliographicCitationJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME, v.135, no.1, pp 1 - 8-
dc.citation.titleJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME-
dc.citation.volume135-
dc.citation.number1-
dc.citation.startPage1-
dc.citation.endPage8-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasssci-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaAutomation & Control Systems-
dc.relation.journalResearchAreaInstruments & Instrumentation-
dc.relation.journalWebOfScienceCategoryAutomation & Control Systems-
dc.relation.journalWebOfScienceCategoryInstruments & Instrumentation-
dc.subject.keywordPlusDESIGN-
dc.subject.keywordPlusMANIPULATORS-
dc.subject.keywordPlusROBOTS-
dc.subject.keywordAuthorACCELERATION-
dc.subject.keywordAuthorDESIGN-
dc.subject.keywordAuthorMANIPULATORS-
dc.subject.keywordAuthorROBOTS-
dc.identifier.urlhttps://asmedigitalcollection.asme.org/dynamicsystems/article/135/1/011001/473828/Convolution-Based-Trajectory-Generation-Methods-
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