Action Understanding and Imitation Learning in a Robot-Human Task
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.
KeywordsPath Planning Control Architecture Precision Grip Goal Representation Action Understanding
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