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dc.contributor.authorNah, Moses C.
dc.contributor.authorKrotov, Aleksei
dc.contributor.authorRusso, Marta
dc.contributor.authorSternad, Dagmar
dc.contributor.authorHogan, Neville
dc.date.accessioned2024-01-19T20:11:38Z
dc.date.available2024-01-19T20:11:38Z
dc.date.issued2023-08
dc.identifier.issn2589-0042
dc.identifier.urihttps://hdl.handle.net/1721.1/153386
dc.description.abstractThis simulation study investigated whether a 4-degrees-of-freedom (DOF) arm could strike a target with a 50-DOF whip using a motion profile similar to discrete human movements. The interactive dynamics of the multi-joint arm was modeled as a constant joint-space mechanical impedance, with values derived from experimental measurement. Targets at various locations could be hit with a single maximally smooth motion in joint-space coordinates. The arm movements that hit the targets were identified with fewer than 250 iterations. The optimal actions were essentially planar arm motions in extrinsic task-space coordinates, predominantly oriented along the most compliant direction of both task-space and joint-space mechanical impedances. Of the optimal movement parameters, striking a target was most sensitive to movement duration. This result suggests that the elementary actions observed in human motor behavior may support efficient motor control in interaction with a dynamically complex object.en_US
dc.language.isoen
dc.publisherElsevier BVen_US
dc.relation.isversionof10.1016/j.isci.2023.107395en_US
dc.rightsCreative Commons Attribution Noncommercial No Derivativesen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourceScience Directen_US
dc.subjectMultidisciplinaryen_US
dc.titleLearning to manipulate a whip with simple primitive actions – A simulation studyen_US
dc.typeArticleen_US
dc.identifier.citationNah, Moses C., Krotov, Aleksei, Russo, Marta, Sternad, Dagmar and Hogan, Neville. 2023. "Learning to manipulate a whip with simple primitive actions – A simulation study." iScience, 26 (8).
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciences
dc.relation.journaliScienceen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2024-01-19T19:51:19Z
dspace.orderedauthorsNah, MC; Krotov, A; Russo, M; Sternad, D; Hogan, Nen_US
dspace.date.submission2024-01-19T19:51:23Z
mit.journal.volume26en_US
mit.journal.issue8en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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