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.
翻译:在受限且杂乱的空间中对水下机器人进行定位,仍然是现场作业面临的关键挑战。现有系统大多针对开阔水域设计,在工业环境中因覆盖范围有限、依赖外部基础设施以及需要特征丰富的周围环境而难以适用。持续的声反射引起的多径效应进一步降低了信号质量,影响了定位的精度与可靠性。精确且易于部署的定位对于可重复的自主任务至关重要,然而这一需求已成为限制水下机器人应用的技术瓶颈。本文提出协作式水下定位(CAP)系统,该系统融合协作机器人技术与传感器融合方法以克服上述局限。受“母舰”概念启发,水面航行器作为移动引导者协助水下机器人定位,即使在GPS拒止及高度受限的环境中也能实现定位。该系统在大型测试水池中通过可重复的自主任务进行了验证,利用CAP的位置估计实现实时轨迹控制。实验结果表明,系统在不依赖固定基础设施、无需大量校准或环境特征的前提下,实时实现了70毫米的平均欧几里得距离(MED)误差。CAP借助移动机器人感知与引导-跟随控制的技术进展,为精确、实用且无需基础设施的水下定位带来了突破性进展。