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Body trajectory generation using quadratic programming in bipedal robots

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dc.contributor.authorMin. InJoon-
dc.contributor.authorYoo. DongHa-
dc.contributor.authorAhn. MinSung-
dc.contributor.authorHan. Jeakweon-
dc.date.accessioned2021-06-22T09:10:51Z-
dc.date.available2021-06-22T09:10:51Z-
dc.date.created2021-01-22-
dc.date.issued2020-10-
dc.identifier.issn1598-7833-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/1499-
dc.description.abstractThe preview control walking method, which is commonly used in bipedal walking, requires jerk and ZMP errors as cost functions to generate body trajectory. Since the two inputs are dependent, optimization to form body trajectory is performed simultaneously with weight factors. Therefore, it is often seen that the resulting body trajectory rapidly changes on velocity according to the weight factors. This eventually requires a torque actuator in order to perform such action. In order to overcome this problem, we apply a method used on a quadruped to a bipedal robot. Since, it only targets to minimize the acceleration of the body trajectory, the body does not require rapid speed change. Also, this method can eliminate the computation time needed for preview control referred to preview time. When applying a quadruped robots walking method that has a relatively large support polygon than that of a bipedal robot, stability deterioration may occur. Therefore, we approached to secure ZMP constraints with relatively small support polygon area as within bipedal robots. In this paper we propose a body trajectory generation method that guarantees real-time stability while minimizing acceleration. © 2020 Institute of Control, Robotics, and Systems - ICROS.-
dc.language영어-
dc.language.isoen-
dc.publisherIEEE Computer Society-
dc.titleBody trajectory generation using quadratic programming in bipedal robots-
dc.typeArticle-
dc.contributor.affiliatedAuthorHan. Jeakweon-
dc.identifier.doi10.23919/ICCAS50221.2020.9268204-
dc.identifier.scopusid2-s2.0-85098069525-
dc.identifier.wosid000681746000041-
dc.identifier.bibliographicCitationInternational Conference on Control, Automation and Systems, v.2020-October, pp.251 - 257-
dc.relation.isPartOfInternational Conference on Control, Automation and Systems-
dc.citation.titleInternational Conference on Control, Automation and Systems-
dc.citation.volume2020-October-
dc.citation.startPage251-
dc.citation.endPage257-
dc.type.rimsART-
dc.type.docTypeConference Paper-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaAutomation & Control Systems-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaRobotics-
dc.relation.journalWebOfScienceCategoryAutomation & Control Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.relation.journalWebOfScienceCategoryRobotics-
dc.subject.keywordPlusBiped locomotion-
dc.subject.keywordPlusCost functions-
dc.subject.keywordPlusDeterioration-
dc.subject.keywordPlusQuadratic programming-
dc.subject.keywordPlusRobot programming-
dc.subject.keywordPlusTrajectories-
dc.subject.keywordPlusBipedal walking-
dc.subject.keywordPlusComputation time-
dc.subject.keywordPlusPreview control-
dc.subject.keywordPlusQuadruped Robots-
dc.subject.keywordPlusSupport polygon-
dc.subject.keywordPlusTorque actuators-
dc.subject.keywordPlusTrajectory generation-
dc.subject.keywordPlusTrajectory generation method-
dc.subject.keywordPlusRobots-
dc.subject.keywordAuthorBipedal robot-
dc.subject.keywordAuthorBody trajectory generation-
dc.subject.keywordAuthorQuadratic Programming-
dc.subject.keywordAuthorZMP optimization-
dc.identifier.urlhttps://ieeexplore.ieee.org/document/9268204?arnumber=9268204&SID=EBSCO:edseee-
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Han, Jea kweon
ERICA 공학대학 (DEPARTMENT OF ROBOT ENGINEERING)
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