Docking and Persistent Operations for a Resident Underwater Vehicle

2026-02-18

AI Summary

This study addresses the longstanding challenges of high cost and logistical complexity that have hindered wide-area, sustained underwater ocean observation. The authors propose a resident underwater robotic system featuring a docking station deployed at 90-meter depth, integrated with a miniature remotely operated vehicle (ROV) capable of autonomous navigation, docking, and rapid inspection without surface support. For the first time in a real deep-sea environment, the system fuses ultra-short baseline (USBL) acoustic positioning with ArUco visual markers, employing an extended Kalman filter for multisensor localization fusion and incorporating an enhanced onboard processing unit. Experimental results demonstrate a 90% success rate in autonomous docking and completion of full inspection missions within four minutes, thereby validating the feasibility, reliability, and scalability of untethered deep-water operations.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Multiagent Systems: Multiagent Systems under Uncertainty

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Vertical and domain-specific search

Abstract

Our understanding of the oceans remains limited by sparse and infrequent observations, primarily because current methods are constrained by the high cost and logistical effort of underwater monitoring, relying either on sporadic surveys across broad areas or on long-term measurements at fixed locations. To overcome these limitations, monitoring systems must enable persistent and autonomous operations without the need for continuous surface support. Despite recent advances, resident underwater vehicles remain uncommon due to persistent challenges in autonomy, robotic resilience, and mechanical robustness, particularly under long-term deployment in harsh and remote environments. This work addresses these problems by presenting the development, deployment, and operation of a resident infrastructure using a docking station with a mini-class Remotely Operated Vehicle (ROV) at 90m depth. The ROVis equipped with enhanced onboard processing and perception, allowing it to autonomously navigate using USBL signals, dock via ArUco marker-based visual localisation fused through an Extended Kalman Filter, and carry out local inspection routines. The system demonstrated a 90% autonomous docking success rate and completed full inspection missions within four minutes, validating the integration of acoustic and visual navigation in real-world conditions. These results show that reliable, untethered operations at depth are feasible, highlighting the potential of resident ROV systems for scalable, cost-effective underwater monitoring.

Problem

• underwater monitoring
• resident underwater vehicle
• autonomous docking
• persistent operations
• robotic resilience

Innovation

• autonomous docking
• resident underwater vehicle
• multi-sensor fusion
• visual-inertial navigation
• persistent ocean monitoring