Deep Reinforcement Learning for sim-to-real policy transfer of VTOL-UAVs offshore docking operations

Ali Mohamed Ali, Aryaman Gupta, Hashim A. Hashim

Abstract: Highlights•Novel deep reinforcement learning for VTOL-UAV docking.•Successful VTOL-UAV landing on uncertain offshore docking stations.•Generalized policy for sim-to-real transfer introduced to increase the success rates in landing operations.•DRL agents learn using a virtual environment subjected to a randomized disturbance describing the hydrodynamics waves.•A set of policy-based and value-based DRL agents are tested against randomized disturbance.