Routing and Control for Marine Oil-Spill Cleanup with a Boom-Towing Vessel Fleet

TL;DR

This paper presents a scalable multi-robot framework for coordinated oil spill cleanup using autonomous surface vessels, optimizing routing and control to minimize environmental damage efficiently.

Contribution

It introduces a hybrid optimization method for multi-spill response planning and analyzes two control strategies for boom-towing ASV duos, enabling effective large-scale spill management.

Findings

Near-optimal routing plans generated within minutes for multiple spills.

Both control strategies achieve accurate boom path tracking in simulations.

Framework demonstrates scalability and risk-awareness for large-scale oil spill response.

Abstract

Marine oil spills damage ecosystems, contaminate coastlines, and disrupt food webs, while imposing substantial economic losses on fisheries and coastal communities. Prior work has demonstrated the feasibility of containing and cleaning individual spills using a duo of autonomous surface vehicles (ASVs) equipped with a towed boom and skimmers. However, existing algorithmic approaches primarily address isolated slicks and individual ASV duos, lacking scalable methods for coordinating large robotic fleets across multiple spills representative of realistic oil-spill incidents. In this work, we propose an integrated multi-robot framework for coordinated oil-spill confinement and cleanup using autonomous ASV duos. We formulate multi-spill response as a risk-weighted minimum-latency problem, where spill-specific risk factors and service times jointly determine cumulative environmental damage. To solve this problem, we develop a hybrid optimization approach combining mixed-integer linear programming, and a tailored warm-start heuristic, enabling near-optimal routing plans for scenarios with tens of spills within minutes on commodity hardware. For physical execution, we design and analyze two tracking controllers for boom-towing ASV duos: a feedback-linearization controller with proven asymptotic stability, and a baseline PID controller. Simulation results under coupled vessel-boom dynamics demonstrate accurate path tracking for both controllers. Together, these components provide a scalable, holistic framework for rapid, risk-aware multi-robot response to large-scale oil spill disasters.