Learning Control of Compensative Trunk Motion for Biped Walking Robot based on ZMP Stability Criterion.

摘要

The authors have been using the ZMP (Zero Moment Point) as a criterion to distinguish the stability of walking for a biped walking robot that has a trunk. In this paper, the authors propose a learning control algorithm of the compensative trunk motion that makes the actual ZMP get closer to the desired ZMP. The convergency of the algorithm is confirmed by computer simulation.