Adaptive predictive gaze control of a redundant humanoid robot head

Abstract

A general concept for the gaze control of a redundant humanoid robot head is presented. It is based on an adaptive Kalman filter that predicts the next state of the moving target, processing the position information provided by a head-mounted stereo camera. The trajectory tracking control at the task level combines a proportional feedback and a feedforward term. The gains of both control actions are adapted in order to provide optimal dynamic response for unknown arbitrary target trajectories. Inverse differential kinematics is evaluated so that human-like joint motions are achieved. To exploit kinematic redundancy, a weighted pseudoinverse is realized that takes into account different optimization criteria. Additional self-motions of the head are also considered. Experimental results on the head of the humanoid robot ARMAR-III are presented.