让潜水机器人自动巡检鱼网，提升养殖效率
A Navigation System for ROV's inspection on Fish Net Cage
- 基于ROS改造蓝海ROV2，集成定位与路径规划
- 实测在实验室环境下实现精准轨迹跟踪
- 适合智能水产养殖与无人设备研发人员
自主遥控潜水器（ROV）为自动化鱼网巡检提供了可行方案，可降低人力依赖并提升作业效率。本文将现成的BlueROV2改装为基于ROS的系统，开发了定位模块、路径规划系统和控制框架。采用开源TagSLAM库实现实时局部定位，并提出基于名义反馈控制器（NFC）的控制策略，以实现精确轨迹跟踪。所提系统已在受控实验室环境中完成实现与验证，证明其在实际应用中的有效性。
原文摘要 · Abstract (English)
Autonomous Remotely Operated Vehicles (ROVs) offer a promising solution for automating fishnet inspection, reducing labor dependency, and improving operational efficiency. In this paper, we modify an off-the-shelf ROV, the BlueROV2, into a ROS-based framework and develop a localization module, a path planning system, and a control framework. For real-time, local localization, we employ the open-source TagSLAM library. Additionally, we propose a control strategy based on a Nominal Feedback Controller (NFC) to achieve precise trajectory tracking. The proposed system has been implemented and validated through experiments in a controlled laboratory environment, demonstrating its effectiveness for real-world applications.
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