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dc.contributor.authorUgur, E.
dc.contributor.authorCelikkanat, H.
dc.contributor.authorŞahin, E.
dc.contributor.authorNagai, Y.
dc.contributor.authorÖztop, Erhan
dc.date.accessioned2016-02-11T14:25:49Z
dc.date.available2016-02-11T14:25:49Z
dc.date.issued2011
dc.identifier.isbn978-1-61284-868-6
dc.identifier.urihttp://hdl.handle.net/10679/2138
dc.identifier.urihttp://ieeexplore.ieee.org/document/6100890/?arnumber=6100890
dc.descriptionDue to copyright restrictions, the access to the full text of this article is only available via subscription.
dc.description.abstractParental scaffolding is an important mechanism utilized by infants during their development. Infants, for example, pay stronger attention to the features of objects highlighted by parents and learn the way of manipulating an object while being supported by parents. In this paper, a robot with the basic ability of reaching for an object, closing fingers and lifting its hand lacks knowledge of which parts of the object affords grasping, and in which hand orientation should the object be grasped. During reach and grasp attempts, the movement of the robot hand is modified by the human caregiver's physical interaction to enable successful grasping. The object regions that the robot fingers contact first are detected and stored as potential graspable object regions along with the trajectory of the hand. In the experiments, we showed that although the human caregiver did not directly show the graspable regions, the robot was able to find regions such as handles of the mugs after its action execution was partially guided by the human. Later, this experience was used to find graspable regions of never seen objects. At the end, the robot was able to grasp objects based on the position of the graspable part and stored action execution trajectories.
dc.description.sponsorshipMinistry of Education, Culture, Sports, Science and Technology, Japan ; European Commission ; TÜBİTAK
dc.language.isoengen_US
dc.publisherIEEE
dc.relationinfo:eu-repo/grantAgreement/EC/FP7/21625
dc.relationinfo:turkey/grantAgreement/TUBITAK/109E033
dc.relation.ispartofHumanoid Robots (Humanoids), 2011 11th IEEE-RAS International Conference on
dc.rightsrestrictedAccess
dc.titleLearning to grasp with parental scaffoldingen_US
dc.typeConference paperen_US
dc.peerreviewedyes
dc.publicationstatuspublisheden_US
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID(ORCID 0000-0002-3051-6038 & YÖK ID 45227) Öztop, Erhan
dc.contributor.ozuauthorÖztop, Erhan
dc.identifier.doi10.1109/Humanoids.2011.6100890
dc.subject.keywordsRobot sensing systems
dc.subject.keywordsHumans
dc.subject.keywordsRobot kinematics
dc.subject.keywordsForce
dc.subject.keywordsJoints
dc.subject.keywordsGrasping
dc.identifier.scopusSCOPUS:2-s2.0-84856330207
dc.contributor.authorMale1


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