Uncrewed underwater vehicles (UUVs) are underwater robots that operate without humans inside. Early use cases for the vehicles have included jobs like deep-sea exploration and the disabling of underwater mines. However, UUVs suffer from poor communication and navigation control because of water’s distorting effect. So researchers have begun to develop machine learning techniques that can help UUVs navigate better autonomously.
Perhaps the biggest challenge the researchers are grappling with is the absence of GPS signals, which can’t penetrate beneath the water’s surface. Other types of navigational techniques that rely on cameras are also ineffective, because underwater cameras suffer from low visibility.
Read more in IEEE Spectrum article.