Falling avoidance control of acrobat robot by reinforcement learning

Abstract

In this study a landing control of an acrobat robot is considered and Q-learning method is applied for falling avoidance control. Since the dynamics of the system is changed according to contact conditions to the ground, the system is a typical variable constraint and hybrid system. The state space for the Q-learning consists of discrete mode variable and continuous states. It is shown by numerical simulations that taking a step motion is automatically generated and falling down is avoided properly.