Digital-physical testbed for ship autonomy studies in the Marine Cybernetics Laboratory basin

2025-05-10

AI Summary

Maritime Autonomous Surface Ship (MASS) algorithm validation faces a dual bottleneck: high cost and safety risks associated with full-scale sea trials, and the limited fidelity of pure simulation in reproducing real-world vessel dynamics. Method: This paper proposes a digital-physical hybrid closed-loop verification platform integrating a small-scale model ship, high-fidelity ROS/Gazebo simulation, Unity-based digital twin, embedded onboard control hardware, and multi-source sensor fusion. It introduces an extensible three-tier validation architecture—laboratory-scale model → semi-physical milliAmpere 1 testbed → full-scale Gunnerus vessel—and employs a real-time communication and synchronization framework to enable tight cyber-physical loop closure. Contribution/Results: The platform has successfully enabled stable deployment and validation of guidance, navigation, and control (GNC) algorithms in laboratory basin tests. It significantly reduces reliance on costly and risky sea trials, accelerates MASS algorithm iteration, and supports rigorous verification and validation (V&V). The approach establishes a reusable, scalable technical paradigm for trustworthy autonomous maritime system certification.

Technology Category

• Multiagent Systems: Multiagent Planning
• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Mixed Discrete/Continuous Planning

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content

Abstract

The algorithms developed for Maritime Autonomous Surface Ships (MASS) are often challenging to test on actual vessels due to high operational costs and safety considerations. Simulations offer a cost-effective alternative and eliminate risks, but they may not accurately represent real-world dynamics for the given tasks. Utilizing small-scale model ships and robotic vessels in conjunction with a laboratory basin provides an accessible testing environment for the early stages of validation processes. However, designing and developing a model vessel for a single test can be costly and cumbersome, and often researchers lack availability to such infrastructure. To address these challenges and enable streamlined testing, we have developed an in-house testbed that facilitates the development, testing, verification, and validation of MASS algorithms in a digital-physical laboratory. This infrastructure includes a set of small-scale model vessels, a simulation environment for each vessel, a comprehensive testbed environment, and a digital twin in Unity. With this, we aim to establish a full design and verification pipeline that starts with high-fidelity simulation models of each model vessel, to the model-scale testing in the laboratory basin, allowing possibilities for moving to semi-fullscale validation with the R/V milliAmpere 1 passenger ferry and full-scale validation using the R/V Gunnerus. In this work, we present our progress on the development of this testbed environment and its components, demonstrating its effectiveness in enabling ship guidance, navigation, and control (GNC) including autonomy.

Problem

• Testing MASS algorithms on actual vessels is costly and unsafe
• Simulations lack real-world accuracy for maritime autonomy tasks
• Small-scale model ships are expensive and inaccessible for single tests

Innovation

• Digital-physical testbed for MASS algorithm validation
• Small-scale model ships with simulation environment
• Digital twin in Unity for high-fidelity testing