Learning Push Recovery Strategies for Bipedal Walking

Abstract

The present work provides an implementation of a Push Recovery controller that aids the walking engine used by a humanoid simulated robot. The simulation environment is the Robocup Soccer 3D Simulation League. The learned movement policies exceeded our original walking engine. In addition, we evaluated the policies and detected undesired biases. New methodologies were introduced in order to eliminate it.