Publication: Learning to grasp with parental scaffolding
dc.contributor.author | Ugur, E. | |
dc.contributor.author | Celikkanat, H. | |
dc.contributor.author | Şahin, E. | |
dc.contributor.author | Nagai, Y. | |
dc.contributor.author | Öztop, Erhan | |
dc.contributor.department | Computer Science | |
dc.contributor.ozuauthor | ÖZTOP, Erhan | |
dc.date.accessioned | 2016-02-11T14:25:49Z | |
dc.date.available | 2016-02-11T14:25:49Z | |
dc.date.issued | 2011 | |
dc.description | Due to copyright restrictions, the access to the full text of this article is only available via subscription. | |
dc.description.abstract | Parental 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.sponsorship | Ministry of Education, Culture, Sports, Science and Technology, Japan ; European Commission ; TÜBİTAK | |
dc.identifier.doi | 10.1109/Humanoids.2011.6100890 | |
dc.identifier.isbn | 978-1-61284-868-6 | |
dc.identifier.scopus | 2-s2.0-84856330207 | |
dc.identifier.uri | http://hdl.handle.net/10679/2138 | |
dc.identifier.uri | https://doi.org/10.1109/Humanoids.2011.6100890 | |
dc.language.iso | eng | en_US |
dc.peerreviewed | yes | |
dc.publicationstatus | published | en_US |
dc.publisher | IEEE | |
dc.relation | info:eu-repo/grantAgreement/EC/FP7/21625 | |
dc.relation | info:turkey/grantAgreement/TUBITAK/109E033 | |
dc.relation.ispartof | Humanoid Robots (Humanoids), 2011 11th IEEE-RAS International Conference on | |
dc.relation.publicationcategory | International | |
dc.rights | info:eu-repo/semantics/restrictedAccess | |
dc.subject.keywords | Robot sensing systems | |
dc.subject.keywords | Humans | |
dc.subject.keywords | Robot kinematics | |
dc.subject.keywords | Force | |
dc.subject.keywords | Joints | |
dc.subject.keywords | Grasping | |
dc.title | Learning to grasp with parental scaffolding | en_US |
dc.type | Conference paper | en_US |
dspace.entity.type | Publication | |
relation.isOrgUnitOfPublication | 85662e71-2a61-492a-b407-df4d38ab90d7 | |
relation.isOrgUnitOfPublication.latestForDiscovery | 85662e71-2a61-492a-b407-df4d38ab90d7 |