Deep Drifting: Autonomous Drifting of Arbitrary Trajectories using Deep Reinforcement Learning
Fabian Domberg,Carlos Castelar Wembers,Hiren Patel,Georg Schildbach,Fabian Domberg,Carlos Castelar Wembers,Hiren Patel,Georg Schildbach
In this paper, a Deep Neural Network is trained using Reinforcement Learning in order to drift on arbitrary trajectories which are defined by a sequence of waypoints. In a first step, a highly accurate vehicle simulation is used for the training process. Then, the obtained policy is refined and validated on a self-built model car. The chosen reward function is inspired by the scoring process of re...
