Learning Control for a Biped Walking Robot with a Trunk.

Abstract

In this paper, the authors propose a learning control method of the compensative trunk motion for a biped walking robot which has a trunk, based on the ZMP (Zero Moment Point) stability criterion , for the cases of the ZMP within and outside the stable region. And the authors develop a biped walking robot with a ZMP measurement system and a support device . By computer simulation and learning control experiments, the authors confirmed the convergency of the learning method and the change of the convergence rate with the change of the weight coefficient. By the learning control experiments for the case of ZMP outside the stable region, the authors showed that even though the walking state of the robot itself changes, by supporting it with a human and its learning with the ZMP and the support force, stable walking even without the support of a human is realized at last.