This Project focuses on improving the ability of unmanned vehicles (UUVs) to accurately determine their position and orientation while operating in offshore aquaculture environments. Reliable localisation is essential for enabling autonomous underwater operations. However, this remains a significant challenge due to the absence of GPS signal underwater, low visibility and continuously changing ocean conditions.

The Project explores how sensor fusion principles can be used to enhance localisation performance by combining information from multiple data sources. The project seeks to understand current limitations in underwater localisation systems and identify opportunities to improve reliability, accuracy, and robustness in offshore aquaculture settings.

The ultimate aim is to support the development of a flexible localisation framework that will enable UUVs to navigate more safely and efficiently around aquaculture infrastructure such as net cages, mooring system and equipment. Improved localisation will contribute to more autonomous underwater operations, reducing the need for constant human supervision and manual control.

This research will play a key role in advancing automation within offshore aquaculture by supporting safer inspections, better structural monitoring, and more efficient operational planning. By strengthening the localisation capability of UUVs, the project contributes to the broader goal of sustainable, technology-driven aquaculture and smarter management of marine environment.