Enabling scalable inspection of offshore mooring systems using cost-effective autonomous underwater drones

As aquaculture expands to meet global food demand, it remains dependent on manual, costly, infrequent, and high-risk operations due to reliance on high-end Remotely Operated Vehicles (ROVs). Scalable and autonomous systems are needed to enable safer and more efficient practices. This paper proposes a cost-effective autonomous inspection framework for the monitoring of mooring systems, a critical component ensuring structural integrity and regulatory compliance for both the aquaculture and floating offshore wind (FOW) sectors. The core contribution of this paper is a modular and scalable vision-based inspection pipeline built on the open-source Robot Operating System 2 (ROS 2) and implemented on a low-cost Blueye X3 underwater drone. The system integrates real-time image enhancement, YOLOv5-based object detection, and 4-DOF visual servoing for autonomous tracking of mooring lines. Additionally, the pipeline supports 3D reconstruction of the observed structure using tools such as ORB-SLAM3 and Meshroom, enabling future capabilities in change detection and defect identification. Validation results from simulation, dock and sea trials showed that the underwater drone can effective inspect of mooring system critical components with real-time processing on edge hardware. A cost estimation for the proposed approach showed a substantial reduction as compared with traditional ROV-based inspections. By increasing the Level of Autonomy (LoA) of off-the-shelf drones, this work provides (1) safer operations by replacing crew-dependent and costly operations that require a ROV and a mothership, (2) scalable monitoring and (3) regulatory-ready documentation. This offers a practical, cross-industry solution for sustainable offshore infrastructure management.