Sim-to-reality adaptation for Deep Reinforcement Learning applied to an underwater docking application

Alaaeddine Chaarani, Narcis Palomeras, Pere Ridao

Deep Reinforcement Learning (DRL) offers a robust alternative to traditional control methods for autonomous underwater docking, particularly in adapting to unpredictable environmen…