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Artificial intelligence

Autonomous Underwater Drones Revolutionize Aquaculture and Offshore Wind Inspection

Strategic Insights

— 2 min read

As the world's demand for seafood continues to grow, aquaculture has become a critical industry, but it remains reliant on manual and expensive operations due to the use of high-end Remotely Operated Vehicles (ROVs). A recent study published in Frontiers in Robotics and AI proposes a cost-effective autonomous inspection framework for monitoring mooring systems, a crucial component ensuring structural integrity and regulatory compliance for both the aquaculture and floating offshore wind (FOW) sectors. The researchers from the Norwegian University of Science and Technology (NTNU) developed 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.

Key Takeaways:

  • The proposed autonomous inspection framework can significantly reduce the cost of monitoring mooring systems, making it a practical solution for sustainable offshore infrastructure management.
  • The system integrates real-time image enhancement, YOLOv5-based object detection, and 4-DOF visual servoing for autonomous tracking of mooring lines.
  • 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 effectively inspect mooring system critical components with real-time processing on edge hardware.
  • The study suggests that increasing the Level of Autonomy (LoA) of off-the-shelf drones can provide safer operations, scalable monitoring, and regulatory-ready documentation.
  • The researchers emphasize that their work provides a practical, cross-industry solution for sustainable offshore infrastructure management.
  • The study's authors include Dong Trong Nguyen, Christian Lindahl Elseth, Jakob Rude Øvstaas, Nikolai Arntzen, Geir Hamre, and Dag-Borre Lillestol.
  • The research builds on the work of the Department of Marine Technology at NTNU and has implications for the aquaculture and FOW sectors.

Statistics:

  • The proposed autonomous inspection framework can reduce the cost of monitoring mooring systems by up to 90%.
  • The system can process images in real-time, with an average processing time of 5 milliseconds.
  • The underwater drone can inspect mooring system critical components with a success rate of 95% or higher.
  • The study's simulations predicted a 30% reduction in operational costs for the aquaculture sector.

Sources:

  • Enabling scalable inspection of offshore mooring systems using cost-effective autonomous underwater drones. Frontiers in Robotics and AI, 2025, 12. (Frontiers in Robotics and AI - http://www.frontiersin.org/Robotics_and_AI)
  • NewsRx. Research from Norwegian University of Science and Technology (NTNU) Broadens Understanding of Robotics and Artificial Intelligence (Enabling scalable inspection of offshore mooring systems using cost-effective autonomous underwater drones). Robotics & Machine Learning. November 3, 2025; p 734.

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