Abstract
We report results of an interdisciplinary project which aims at endowing a real robot system with the capacity for learning by goal-directed 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.
The work was supported by the European grantArteSImit (IST-2000-29686). We would like to thank Drs Leonardo Fogassi and Giacomo Rizzolatti for numerous discussions about this work.
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Erlhagen, W. et al. (2005). Action Understanding and Imitation Learning in a Robot-Human Task. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_42
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DOI: https://doi.org/10.1007/11550822_42
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