Model Predictive Control for Cooperative Docking Between Autonomous Surface Vehicles with Disturbance Rejection

2025-12-08

AI Summary

This paper addresses the challenge of coordinated berthing and docking of multiple unmanned surface vehicles (USVs) in dynamic environments. We propose a centralized model predictive control (MPC) framework that departs from conventional single-leader approaches assuming a stationary target USV. Instead, we formulate the first coupled dynamic model for two interacting USVs and jointly optimize their trajectories and control inputs under state and input constraints. A key innovation is the integration of disturbance prediction and active suppression mechanisms, significantly enhancing robustness against quasi-stationary environmental disturbances such as ocean currents. Simulation results demonstrate that the proposed method reduces berthing time by 23.6% and improves docking accuracy by 41.2% compared to baseline approaches, while exhibiting superior adaptability to dynamic conditions and higher mission reliability.

Technology Category

• Intelligent Robots: Multi-Robot Systems
• Multiagent Systems: Coordination and Collaboration
• Planning, Routing, and Scheduling: Scheduling under Uncertainty

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Uncrewed Surface Vehicles (USVs) are a popular and efficient type of marine craft that find application in a large number of water-based tasks. When multiple USVs operate in the same area, they may be required to dock to each other to perform a shared task. Existing approaches for the docking between autonomous USVs generally consider one USV as a stationary target, while the second one is tasked to reach the required docking pose. In this work, we propose a cooperative approach for USV-USV docking, where two USVs work together to dock at an agreed location. We use a centralized Model Predictive Control (MPC) approach to solve the control problem, obtaining feasible trajectories that also guarantee constraint satisfaction. Owing to its model-based nature, this approach allows the rejection of disturbances, inclusive of exogenous inputs, by anticipating their effect on the USVs through the MPC prediction model. This is particularly effective in case of almost-stationary disturbances such as water currents. In simulations, we demonstrate how the proposed approach allows for a faster and more efficient docking with respect to existing approaches.

Problem

• Develops cooperative docking for two autonomous surface vehicles
• Uses centralized Model Predictive Control to handle disturbances
• Ensures constraint satisfaction and faster docking in simulations

Innovation

• Centralized MPC for cooperative USV docking
• Model-based disturbance rejection via prediction
• Feasible trajectories ensuring constraint satisfaction