ORIGINAL RESEARCH article
Front. Robot. AI
Sec. Field Robotics
Volume 12 - 2025 | doi: 10.3389/frobt.2025.1655242
This article is part of the Research TopicAutonomous Robotic Systems in Aquaculture: Research Challenges and Industry NeedsView all 4 articles
Enabling Scalable Inspection of Offshore Mooring Systems Using Cost-Effective Autonomous Underwater Drones
Provisionally accepted
Dong Trong Nguyen1*
Christian Lindahl Elseth1
Jakob Rude Øvstaas1Nikolai Arntzen1Geir Hamre2Dag-Børre Lillestøl2- 1Norwegian University of Science and Technology, Trondheim, Norway
- 2DNV AS, Høvik, Norway
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As aquaculture expands to meet global food demand, it remains dependent on manual, costly, 3 infrequent, and high-risk operations due to reliance on high-end Romotely Operated Vehicles 4 (ROVs). Scalable and autonomous systems are needed to enable safer and more efficient 5 practices. This paper proposes a cost-efficient autonomous inspection framework for monitoring 6 of mooring system — a critical component ensuring structural integrity and regulatory compliance 7 for both aquaculture and floating offshore wind (FOW) sectors. The core contribution of this 8 paper is a modular and scalable vision-based inspection pipeline built on open-source Robot 9 Operating System 2 (ROS 2) and implemented on a low-cost Blueye X3 underwater drone. The 10 system integrates real-time image enhancement, YOLOv5-based object detection, and 4-DOF 11 visual servoing for autonomous tracking of mooring lines. Additionally, the pipeline supports 12 3D reconstruction of the observed structure using tools such as ORB-SLAM3 and Meshroom, 13 enabling future capabilities in change detection and defect identification. Validation results from 14 simulation, dock and sea trials showed that the underwater drone can effective inspect of 15 mooring system critical components with real-time processing on edge hardware. An indicated 16 cost estimation for the proposed approach showed a substantial reduction as compared to a 17 traditional ROV-based inspection. By increasing the Level of Autonomy (LoA) of off-the-shelf 18 drones, this work provides (1) safer operations by replacing crew-dependent and costly operation 19 of Remotely Operated Vehicle (ROV) and a mothership, (2) scalable monitoring and (3) regulatory-20 ready documentation. This offers a practical, cross-industry solution for sustainable offshore 21 infrastructure management.
Keywords: Autonomous Underwater, Drones, cost effective, Aquaculture, Maintenance & inspection, Computer Vision, Path following
Received: 27 Jun 2025; Accepted: 25 Aug 2025.
Copyright: © 2025 Nguyen, Elseth, Øvstaas, Arntzen, Hamre and Lillestøl. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dong Trong Nguyen, Norwegian University of Science and Technology, Trondheim, Norway
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