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

Snir Carmeli, Adir Morgan, Kiril Solovey

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.

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

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.
Paper Structure (24 sections, 1 theorem, 52 equations, 7 figures)

This paper contains 24 sections, 1 theorem, 52 equations, 7 figures.

Table of Contents

  1. Introduction
  2. Related Work
  3. Damage-Aware Routing and Tracking model
  4. System and Response Model
  5. Damage Accumulation as Latency Objective
  6. Motion-Based Graph Representation
  7. Damage-Minimizing Routing Problem
  8. Trajectory Tracking Control Problem
  9. Solving Damage-Minimizing Routing
  10. MILP Formulation for DMR
  11. Warm-start Heuristic
  12. Dynamics of a boom-towing ASV duo
  13. Single ASV dynamics
  14. Boom dynamics
  15. Combined duo-boom dynamics
  16. ...and 9 more sections

Key Result

Theorem 1

Consider the feedback-linearized closed-loop dynamics in Equations eq:Linear_EOMs, with the virtual inputs $\alpha_u,\alpha_\omega$ produced by the (normalized) lead controllers Additionally, assume the following: Then, for any initial condition, the tracking errors satisfy $u(t)-u_{\mathrm{ref}}\to 0, \theta(t)-\theta_{\mathrm{ref}}\to 0$, and $v(t)\to 0$, $\qquad\text{as }t\to\infty$.

Figures (7)

  • Figure 1: Visualization of coordinated oil-spill confinement and cleanup using autonomous ASV duos equipped with towed booms and skimmers, which we tackle in this work.
  • Figure 2: Illustration of the path tracking problem for a boom-towing ASV duo, along with feedback-linearization control behavior, presented in Sec. \ref{['sec:PathTracking']}. A reference trajectory generated by the routing approach is converted into a sequence of tracked setpoints (blue dots and red squares) for each individual ASV, while satisfying boom constraints.
  • Figure 3: Body–fixed surge–sway frame $(u,v)$ attached to the vessel’s center of mass (CoM).
  • Figure 4: Visualization for the boom dynamics. Body–fixed surge–sway frame $(t,n)$ attached to the link’s center of mass (CoM); inertial axes point East ($e_1$) and North ($e_2$). The control inputs are the forces and torques applied by nearby linked bodies.
  • Figure 5: Final objective values for 25, 50, and 100 spills instances across varying numbers of agents. Shaded gray regions indicate lower bounds.
  • ...and 2 more figures

Theorems & Definitions (5)

  • Theorem 1: Asymptotic stability
  • Claim 1: Surge and yaw tracking are exponentially stable
  • proof
  • Claim 2: Sway stability under exponentially decaying disturbance
  • proof