Benchmarking Safe Deep Reinforcement Learning in Aquatic Navigation
Enrico Marchesini,Davide Corsi,Alessandro Farinelli,Enrico Marchesini,Davide Corsi,Alessandro Farinelli
We propose a novel benchmark environment for Safe Reinforcement Learning focusing on aquatic navigation. Aquatic navigation is an extremely challenging task due to the non-stationary environment and the uncertainties of the robotic platform, hence it is crucial to consider the safety aspect of the problem, by analyzing the behavior of the trained network to avoid dangerous situations (e.g., collis...
