Dock-to-Dock Motion Control for Autonomous Vessels

Master Thesis (2025)
Author(s)

U.J.M. Coveliers-Munzi (TU Delft - Aerospace Engineering)

Contributor(s)

Erik Jan Kampen – Mentor (TU Delft - Control & Simulation)

Kasper van der El – Mentor (Damen Shipyards)

O. Stroosma – Graduation committee member (TU Delft - International Research Institute for Simulation, Motion and Navigation)

Sherry Wang – Graduation committee member (TU Delft - Group Wang)

Faculty
Aerospace Engineering
More Info
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Publication Year
2025
Language
English
Graduation Date
03-09-2025
Awarding Institution
Delft University of Technology
Programme
['Aerospace Engineering']
Faculty
Aerospace Engineering
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Abstract

Driven by the need to enhance safety, improve efficiency and address labour shortages, autonomous vessel operations are increasingly moving beyond open-water navigation toward more complex missions demanding integration of multiple control strategies. Dock-to-dock operations represent a critical mission encompassing the full spectrum of motion control challenges: long-distance transit, switching between control phases, and precise low-speed maneuvering in confined waters under environmental disturbances.

This thesis evaluates control strategies for autonomous dock-to-dock sailing on inland waterways. A benchmark system using industry standard PID controllers is compared to an all-in-one Reinforcement Learning (RL) controller and a third, hybrid system is proposed trading off the improved performance of the RL controller with the inherent stability guarantees of the benchmark system. Simulation results show all three controllers can successfully perform the mission. The RL controller docks significantly faster while rejecting higher lateral wind forces but struggles to generalise to unseen docking scenarios, while the hybrid system improves interpretability at the cost of performance. Furthermore, initial real-life testing of the benchmark system validates the simulation results.

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