Aquatic Navigation

Aquatic navigation research focuses on developing robust and safe methods for autonomous vehicles to navigate complex underwater and surface environments. Current efforts concentrate on improving control algorithms, particularly through deep reinforcement learning and dynamic programming, often incorporating predictive safety filters and advanced sensor fusion techniques to handle uncertainties and ensure collision avoidance. These advancements are crucial for enhancing the efficiency and safety of maritime operations, including autonomous surface vessels and underwater robotics for tasks like search and rescue and deep-sea exploration. The development of reliable benchmarking environments is also a key area of focus, facilitating the comparison and improvement of different navigation strategies.