Abstract

In the RoboCup 3D simulation competition, how to find a flexible and stable gait pattern is one of the keys to win the match. To achieve such walking gait, a machine learning method of optimizing the vertical Center of Mass(CoM) trajectory is presented. The vertical CoM trajectory is planned by multiple polynomial function. Inverted Pendulum Model(IPM) and a numerical method are utilized to control the Zero Moment Point(ZMP). Then the key parameters are extracted from the gait pattern, a distributed multi-robot training environment based on RoboCup 3D simulated platform is constructed, and the parallel multi-swarm particle swarm algorithm is applied to optimize the parameters. The results of experiment and competition demonstrate that the effectiveness of the proposed method.

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