Autonomous Underwater

Autonomous underwater vehicles (AUVs) are rapidly advancing, driven by the need for efficient and safe underwater operations across diverse applications, from pipeline inspection to oceanographic monitoring and aquaculture. Current research emphasizes developing robust control systems, often leveraging deep reinforcement learning and behavior trees to enable complex tasks like collision avoidance and autonomous sample collection in challenging environments. This work is facilitated by modular robotic platforms and advanced perception systems, including computer vision and sub-bottom acoustic data analysis, ultimately improving the efficiency and safety of underwater exploration and intervention.