发表机构
The University of Auckland（奥克兰大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出一种由无人机部署的3D打印自主浮标AeroBuoy，利用水流和GPS/磁力计导航，可搭载多种传感器，用于偏远危险河流的环境巡检，并在新西兰Ōrewa河完成系统演示。
AI 中文摘要
监测偏远和危险的河流及溪流等水道对于评估外部因素（如建筑径流或气候变化）的影响至关重要。多功能、自主的机器人船可以为偏远、危险或受保护的水体提供出色的环境巡检和监测解决方案，但它们在机动性方面存在若干不足。本文提出了一种环境巡检系统，该系统由一个自主数据采集浮标组成，该浮标设计用于通过无人机部署到难以进入的河流系统中。系统可根据特定地点和监测任务的要求，执行浮标的投放和回收。利用河流的自然水流，浮标自主向下游航行，使用GPS和磁力计以保持期望的轨迹。该浮标能够测量水温，但也可以配备一系列传感器，如水中氧计、用于河床检查的声纳或用于水清澈度的浊度传感器。本文描述了系统设计，对浮标的自动扶正能力进行了分析，并在新西兰奥克兰的Ōrewa河展示了完整的系统演示。
英文摘要
Monitoring of waterways such as remote and hazardous rivers and streams is important so as to assess the impact of external factors including construction runoff or climate change. Versatile, autonomous robotic boats can offer excellent environmental inspection and monitoring solutions for remote, dangerous, or access protected water bodies but they have several shortcomings in terms of maneuverability. This paper proposes an environmental inspection system consisting of an autonomous data collection buoy which is designed to be deployed to inaccessible river systems using a drone. The system can perform a drop off and pickup of the buoy depending on the requirements of a particular location and monitoring task. Utilising the natural flow of the river the buoy autonomously steers down, using GPS and magnetometers so as to maintain the desired trajectory. The buoy is capable of measuring water temperature but it can also be equipped with a range of sensors such as water oxygen meter, sonar for river bed inspection, or turbidity for water clarity. This paper describes the system design, presents an analysis of the self-righting capabilities of the buoy, and shows a full system demonstration at the Ōrewa River in Auckland, New Zealand.
Comments7 pages. Accepted version. Published in the 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Winner of the IROS 2025 Best Paper Award on Safety, Security, and Rescue Robotics in memory of Motohiro Kisoi. Reuben O'Brien and Angus Lynch contributed equally
Journal ref2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hangzhou, China, 2025, pp. 7269-7275
DOI：10.1109/IROS60139.2025.11247654
