Abstract
The formulation and optimization of joint trajectories for humanoid robots is quite different from this same task for standard robots because of the complexity of the humanoid robots' kinematics. We exploit the similarity between the movements of a humanoid robot and human movements to generate joint trajectories for such robots. In particular we show how to transform human motion information captured by an optical tracking device into a high dimensional trajectory of a humanoid robot. We utilize B-spline wavelets to efficiently represent the joint trajectories and to automatically select the density of the basis functions on the time axis. We applied our method to the task of teaching a humanoid robot how to make a dance movement.
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