Simulation of Evolutionary Reinforcement Learning-Based Self-Balancing Throwable One-Legged Robot with a Reaction Wheel

In this paper, the One-Legged robot is designed to stabilize itself and stand upright at the desired location after being thrown from a different heights. The 5-DOF planar underactuated main body is driven by Reaction wheels, and adaptive Cartesian impedance control has been implemented to effectively manage hard impacts. Evolutionary Reinforcement Learning based AI Agent have been used to adapt to different launch conditions, such as varying speed and altitude. The learning process was performed in real-time using the Matlab simulation program, which models the system dynamics of the robot. The graphical results of the simulation confirm that, with the assistance of the AI agent, the dynamic robot has successfully maintained its stability without tipping over after the launch and has been able to make the desired correction.