无需固定设施，水下机器人协同定位误差仅70毫米。
Confined Space Underwater Positioning Using Collaborative Robots
- 水面船作移动领航，协同水下机器人实现定位。
- 实测均方根距离误差70毫米，实时完成轨迹控制。
- 适合无GPS、无特征的狭小水下环境，部署便捷。
在受限且杂乱的水下环境中，机器人精确定位仍是野外作业的关键挑战。现有系统多针对开阔水域设计，在工业场景中因覆盖不足、依赖外部基础设施及对环境特征要求高而表现不佳。连续声波反射导致多路径效应，进一步降低信号质量，影响精度与可靠性。准确且易部署的定位对重复性自主任务至关重要，但这一需求已成为制约水下机器人应用的技术瓶颈。本文提出协同水下定位（CAP）系统，融合协同机器人与传感器融合技术，突破上述限制。受‘母船’概念启发，水面车辆作为移动领导者，协助定位水下机器人，使其在无GPS和高度受限环境中仍可实现定位。系统在大型测试水池中通过重复性自主任务验证，利用CAP的位置估计实现实时轨迹控制。实验结果表明，平均欧氏距离（MED）误差为70毫米，全程无需固定基础设施、复杂校准或环境特征，依托移动机器人感知与领航-跟随控制技术，实现了高精度、实用且无需基础设施的水下定位突破。
原文摘要 · Abstract (English)
Positioning of underwater robots in confined and cluttered spaces remains a key challenge for field operations. Existing systems are mostly designed for large, open-water environments and struggle in industrial settings due to poor coverage, reliance on external infrastructure, and the need for feature-rich surroundings. Multipath effects from continuous sound reflections further degrade signal quality, reducing accuracy and reliability. Accurate and easily deployable positioning is essential for repeatable autonomous missions; however, this requirement has created a technological bottleneck limiting underwater robotic deployment. This paper presents the Collaborative Aquatic Positioning (CAP) system, which integrates collaborative robotics and sensor fusion to overcome these limitations. Inspired by the "mother-ship" concept, the surface vehicle acts as a mobile leader to assist in positioning a submerged robot, enabling localization even in GPS-denied and highly constrained environments. The system is validated in a large test tank through repeatable autonomous missions using CAP's position estimates for real-time trajectory control. Experimental results demonstrate a mean Euclidean distance (MED) error of 70 mm, achieved in real time without requiring fixed infrastructure, extensive calibration, or environmental features. CAP leverages advances in mobile robot sensing and leader-follower control to deliver a step change in accurate, practical, and infrastructure-free underwater localization.
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