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Publication Details

Reference TypeConference Proceedings
Author(s)Billard, A.;Schaal, S.
TitleRobust learning of arm trajectories through human demonstration
Journal/Conference/Book TitleIEEE International Conference on Intelligent Robots and Systems (IROS 2001)
Keywordsimitation learning, movement primitives, humanoid robotics
AbstractWe present a model, composed of hierarchy of artificial neural networks, for robot learning by demonstration. The model is implemented in a dynamic simulation of a 41 degrees of freedom humanoid for reproducing 3D human motion of the arm. Results show that the model requires few information about the desired trajectory and learns on-line the relevant features of movement. It can generalize across a small set of data to produce a qualitatively good reproduction of the demonstrated trajectory. Finally, it is shown that reproduction of the trajectory after learning is robust against perturbations.
Place PublishedMaui, Hawaii, Oct.29-Nov.3
PublisherPiscataway, NJ: IEEE
Short TitleRobust learning of arm trajectories through human demonstration

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