Anti-push Method of Biped Robot Based on Motion Capture Point and Reinforcement Learning

Bipedal humanoid robots are unstable to external perturbations, especially when they are walking on uneven terrain in the presence of unforeseen collisions or obtained a external push force. The motion state capture point balance algorithm, need to adjust many hyper-parameters, and the parameters needed by the robot in different environments are nonlinear. We present a push recovery controller combined with reinforcement learning methond and get optimal parameters of the recovery controller. The experimental results show that our method can achieve the balance control of biped robot, and achieve good adaptability in simulation environment.