Reinforcement Learning for Flight Posture Control of Flapping Robot with Left-and-right Wings Independent Drive System

Abstract

We have developed a reinforcement learning approach for controlling a flapping robot toward autonomous flight control. The flapping robot is equipped with a center-of-gravity (COG) shift mechanism, thereby enabling seamless changes in the flight attitude between hovering and level flights. The yaw angle can be controlled by differentiating flapping frequencies of left and right wings. We demonstrates that reinforcement learning is effecttively utilized to stabilize the hovering flight.