Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/4458

TitleAction understanding and imitation learning in a robot-human task
Author(s)Erlhagen, Wolfram
Mukovskiy, Albert
Bicho, E.
Panin, Giorgio
Kiss, Casba
Knoll, Alois
Van Schie, Hein
Bekkering, Harold
KeywordsImitation learning
Robotics
Dynamic field model
Action understanding
Issue date2005
PublisherSpringer
JournalLecture Notes in Computer Science
CitationDUCH, W. [et al.], ed. – “Artificial neural networks : formal models and their applications - ICANN 2005 : 15th International Conference, Warsaw, Poland, September 11-15, 2005 : proceedings”. Berlin [etc.] : Springer, cop. 2005. ISBN 3-540-28755-8. p. 261-268.
Abstract(s)We report results of an interdisciplinary project which aims at endowing a real robot system with the capacity for learning by goaldirected imitation. The control architecture is biologically inspired as it reflects recent experimental findings in action observation/execution studies. We test its functionality in variations of an imitation paradigm in which the artefact has to reproduce the observed or inferred end state of a grasping-placing sequence displayed by a human model.
TypeconferencePaper
URIhttp://hdl.handle.net/1822/4458
ISBN3-540-28755-8
DOI10.1007/11550822_42
ISSN0302-9743
Peer-Reviewedyes
AccessopenAccess
Appears in Collections:Offmath - Comunicações

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