Goal-directed movement generation with a transient-based recurrent neural network controller
Contributor(s)The Pennsylvania State University CiteSeerX Archives
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AbstractWe introduce a control framework based on a recurrent neural network for goal-directed movement generation. We exploit the network dynamics to implement a nonlinear task space controller. Efficient online learning and execution of the network makes the proposed approach adaptive and real-time capable. We achieve reliable and excellent generalization for the 7-DOF redundant PA-10 robot arm in simulation.