104077Advancing Underwater Vision for 3D (AUV3D)ClosedFeasibility StudiesISCFSafe and efficient construction, operation and decommissioning of subsea assets is critically important to UK and worldwide energy production. This is particularly true for offshore renewable energy where cost efficiencies are necessary to deliver clean power power that is cost competitive with other low carbon systems and at an affordable scale. From construction to decommissioning, underwater survey provides the data to monitor condition, predict asset life and ensure the environment is protected. We aim to deliver a step change in efficiency and safety by delivering live, dense, 3D point cloud data from small, Remotely Operated Underwater Vehicles. This will enable smaller vessels to be used with fewer crew, no divers, and removing the need to put people at risk. Compared to traditional visual survey, 3D data allows accurate measurement and repeatable, reliable metrics for asset condition monitoring. Ultimately, live 3D enables accurate navigation for fully autonomous underwater vehicles reducing manpower and increasing efficiency yet further. Quality 3D visual data is also a prerequisite to applying artificial intelligence and deep learning solutions to 3D images thereby enabling greater autonomy and reliably repeatable measurements. The key objective of the AUV3D project is to prototype and demonstrate the feasibility of a high-quality underwater, intelligent, stereo camera system. This system will enable innovative, real-time processing of underwater 3D from ROV video survey. To do this we will exploit recent advances in both camera technology and embedded GPU computing, and together these technologies enable Artificial Intelligence to be used to accurately to assess underwater 3D scenes. By demonstrating the feasibility of the software and hardware necessary to produce live 3D data from cameras in the challenging and extreme subsea environment we enable the development of a complete vision based underwater Robotic Artificial Intelligence (RAI) survey solution. This has the potential to create small, capable, intelligent autonomous vehicles and allow more efficient survey with fewer people in harm's way.