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ICRA
2002
IEEE

Movement Imitation with Nonlinear Dynamical Systems in Humanoid Robots

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Movement Imitation with Nonlinear Dynamical Systems in Humanoid Robots
This article presents a new approach to movement planning, on-line trajectory modification, and imitation learning by representing movement plans based on a set of nonlinear differential equations with well-defined attractor dynamics. In contrast to non-autonomous movement representations like splines, the resultant movement plan remains an autonomous set of nonlinear differential equations that forms a control policy (CP) which is robust to strong external perturbations and that can be modified on-line by additional perceptual variables. The attractor landscape of the control policy can be learned rapidly with a locally weighted regression technique with guaranteed convergence of the learning algorithm and convergence to the movement target. This property makes the system suitable for movement imitation and also for classifying demonstrated movement according to the parameters of the learning system. We evaluate the system with a humanoid robot simulation and an actual humanoid ...
Auke Jan Ijspeert, Jun Nakanishi, Stefan Schaal
Added 15 Jul 2010
Updated 15 Jul 2010
Type Conference
Year 2002
Where ICRA
Authors Auke Jan Ijspeert, Jun Nakanishi, Stefan Schaal
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