Pitch control with thrust vectoring by using deep reinforcement learning for unmanned aerial vehicle

Abstract

Deep reinforcement learning is applied to the pitch control of the UAV equipped with electric ducted fans and thrust vectoring. A controller is trained to maintain the target attitude even when the system model is uncertain. Through the uniaxial rotation experiment, it was shown that the attitude can be controlled by the deep reinforcement learning-based approach with domain randomization.