Confined Space Underwater Positioning Using Collaborative Robots

TL;DR

The paper introduces the CAP system, a collaborative underwater positioning method using a surface vehicle as a mobile leader, achieving high accuracy in confined, GPS-denied environments without fixed infrastructure.

Contribution

It presents a novel sensor fusion-based system that enables accurate, infrastructure-free underwater localization in confined spaces, validated through real-time autonomous tests.

Findings

Achieved a mean Euclidean distance error of 70 mm in real-time.

Demonstrated effective localization without fixed infrastructure or environmental features.

Validated in a large test tank with repeatable autonomous missions.

Abstract

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.