Opportunistic (Re)planning for Long-Term Deep-Ocean Inspection: An Autonomous Underwater Architecture

Abstract

Robots are increasingly used in subsea environments because of their positive impact on human safety and operational capabilities in the deep ocean. However, achieving full autonomy remains challenging because of the extreme conditions they encounter. In this context, we propose an autonomous underwater architecture for long-term deep-ocean inspection that robustly plans activities and efficiently deliberates with no human help. It combines the innovative Saipem’s Hydrone-R subsea vehicle with an advanced planning architecture, resulting in a robot that autonomously perceives its surroundings, plans a mission, and adapts in real time to contingencies and opportunities. After describing the robot hardware, we present the technological advancements achieved in building its software, along with several compelling use cases. We explore scenarios where the robot conducts long-term underwater missions operating under resource constraints while remaining responsive to opportunities, such as new inspection points. Our solution gained significant reliability and acceptance within the oil and gas community as evidenced by its current deployment on a real field in Norway.