Utilize este identificador para referenciar este registo: http://hdl.handle.net/1822/4458

TítuloAction understanding and imitation learning in a robot-human task
Autor(es)Erlhagen, Wolfram
Mukovskiy, Albert
Bicho, E.
Panin, Giorgio
Kiss, Casba
Knoll, Alois
Van Schie, Hein
Bekkering, Harold
Palavras-chaveImitation learning
Dynamic field model
Action understanding
RevistaLecture Notes in Computer Science
CitaçãoDUCH, 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.
Resumo(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.
Arbitragem científicayes
Aparece nas coleções:Offmath - Comunicações

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