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通过使用具有成本效益的自主水下无人机,实现对海上泊位系统的可扩展检查

Dong Trong Nguyen¹, Christian Lindahl Elseth¹, Jakob Rude Øvstaas¹

¹Department of Marine Technology, Norwegian University of Science and Technology, Trondheim, Norway.

Frontiers in robotics and AI

|November 3, 2025

概括

本研究引入了一种具有成本效益的海上泊水线的自主检查系统,以提高水产养殖和海上风电的安全性和效率. 与传统的远程操作车辆 (ROV) 方法相比,该框架显著降低了成本.

科学领域:

海洋工程海洋工程
机器人技术机器人技术机器人技术
计算机视觉计算机视觉

背景情况:

水产养殖和海上风电行业依赖于手动,高风险的装系统检查,通常使用昂贵的远程操作车辆 (ROV).
迫切需要可扩展,自主和具有成本效益的解决方案来提高海上基础设施监控的安全性和效率.

研究的目的:

提出和验证一个具有成本效益的自主检查框架,用于监测水产养殖和浮动海上风力 (FOW) 部门的系系统.
提高离岸基础设施管理的运营安全,可扩展性和监管合规性.

主要方法:

在低成本的Blueye X3水下无人机上使用机器人操作系统2 (ROS2) 开发一个模块化,基于视觉的检查管道.
集成实时图像增强,YOLOv5对象检测,用于自主跟踪的4-DOF视觉伺服和3D重建 (ORB-SLAM3,Meshroom).
通过模拟,码头和海上试验与实时边缘处理进行验证.

主要成果:

自主系统有效地实时检查关键泊系统组件.
与传统的基于ROV的检查相比,拟议的框架证明了大幅降低成本.
成功验证了现成无人机的自主程度 (LoA) 的提高.

结论:

开发的框架为可持续的海上基础设施监测提供了一个实用,更安全和可扩展的解决方案.
增加的自主性减少了对机组人员依赖的,昂贵的操作的依赖,提供了准备好的监管文件.
这种方法提供了一个跨行业的解决方案,以有效地管理离岸资产.

关键词:

水产养殖的水产养殖自主水下自主潜水系统计算机视觉计算机视觉具有成本效益,具有成本效益.无人机无人机无人机维护和检查以及检查.沿着路径遵循的路径.

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