A team of researchers has successfully demonstrated that deep reinforcement learning can be used to enable underwater autonomous vehicles and robots to accurately locate and track objects and marine animals.
Underwater robotics has become an essential tool for exploring the oceans, allowing vehicles to reach depths of up to 4,000 meters. The data collected by these robots complements other sources of information, such as satellite data, and enables the study of small-scale phenomena like CO2 capture by marine organisms, which is crucial for understanding climate change.
