Human Manipulation Segmentation and Characterization Based on Instantaneous Work

Simple item page
dc.contributor.authorRemazeilles, Anthony
dc.contributor.authorRasines, Irati
dc.contributor.authorFernandez, Asier
dc.contributor.authorMcIntyre, Joseph
dc.contributor.editorSilva, Manuel F.
dc.contributor.editorLuís Lima, José
dc.contributor.editorReis, Luís Paulo
dc.contributor.editorSanfeliu, Alberto
dc.contributor.editorTardioli, Danilo
dc.contributor.institutionRobótica Médica
dc.date.accessioned2024-07-24T11:48:01Z
dc.date.available2024-07-24T11:48:01Z
dc.date.issued2020
dc.descriptionPublisher Copyright: © 2020, Springer Nature Switzerland AG.
dc.description.abstractThis paper is related to the observation of human operator manipulating objects for teaching a robot to reproduce the action. Assuming the robotic system is equipped with basic manipulation skills, we focus here on the automatic segmentation of the observed manipulation, for extracting the relevant key frames in which the manipulation is best described. The segmentation method proposed is based on the instantaneous work, and presents the advantage of not depending on the force and pose sensing locations. The proposed approach is experimented with two different manipulation skills, sliding and folding, under different settings.en
dc.description.sponsorshipAcknowledgements. Supported by the Elkartek MALGUROB and the SARAFun project under the European Union’s Horizon 2020 research & innovation programme, grant agreement No. 644938. The authors would like to thank Dr. Pierre Barralon for the fruitfull discussions that led to the segmentation approach presented here. Supported by the Elkartek MALGUROB and the SARAFun project under the European Union?s Horizon 2020 research & innovation programme, grant agreement No. 644938. The authors would like to thank Dr. Pierre Barralon for the fruitfull discussions that led to the segmentation approach presented here.
dc.description.statusPeer reviewed
dc.format.extent12
dc.identifier.citationRemazeilles , A , Rasines , I , Fernandez , A & McIntyre , J 2020 , Human Manipulation Segmentation and Characterization Based on Instantaneous Work . in M F Silva , J Luís Lima , L P Reis , A Sanfeliu & D Tardioli (eds) , Robot 2019 : 4th Iberian Robotics Conference - Advances in Robotics . Advances in Intelligent Systems and Computing , vol. 1092 AISC , Springer , pp. 343-354 , 4th Iberian Robotics Conference, ROBOT 2019 , Porto , Portugal , 20/11/19 . https://doi.org/10.1007/978-3-030-35990-4_28
dc.identifier.citationconference
dc.identifier.doi10.1007/978-3-030-35990-4_28
dc.identifier.isbn9783030359898
dc.identifier.issn2194-5357
dc.identifier.urihttps://hdl.handle.net/11556/1724
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85082137099&partnerID=8YFLogxK
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofRobot 2019
dc.relation.ispartofseriesAdvances in Intelligent Systems and Computing
dc.relation.projectIDEuropean Union?s Horizon 2020 research & innovation programme
dc.relation.projectIDEuropean Union’s Horizon 2020 research & innovation programme, 644938
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsManipulation segmentation
dc.subject.keywordsTeaching by demonstration
dc.subject.keywordsControl and Systems Engineering
dc.subject.keywordsGeneral Computer Science
dc.titleHuman Manipulation Segmentation and Characterization Based on Instantaneous Worken
dc.typeconference output
Files