Ship manoeuvring research 2010–2025 : from hydrodynamics and control to digital twins, AI and MASS

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Tadros, Mina and Aung, Myo Zin and Louvros, Panagiotis and Pollalis, Christos and Nazemian, Amin and Boulougouris, Evangelos (2025) Ship manoeuvring research 2010–2025 : from hydrodynamics and control to digital twins, AI and MASS. Journal of Marine Science and Engineering, 13 (12). 2322. ISSN 2077-1312 (https://doi.org/10.3390/jmse13122322)

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Abstract

Over the past fifteen years, ship manoeuvring has evolved from a highly specialised branch of marine hydrodynamics into a key enabler within multidisciplinary research, integrating seakeeping and intact stability, and paving the way for digital twins and autonomous maritime systems. The scope of this review is to examine the existing literature in a way that paves the way forward for integration with robotics, aerial and surface drones, digital-twin (DT) ecosystems, and other interconnected autonomous platforms. This paper reviews the published articles during this period, tracing the field’s progression from classical hydrodynamic models to intelligent, data-centric, and regulation-aware maritime systems. Drawing on a structured bibliometric dataset covering 2010–2025, this study organises the literature into interconnected themes spanning physics-based manoeuvring models, adaptive and predictive control, machine learning and digital-twin (DT) technologies, collision-avoidance and regulatory reasoning, environmental performance, and cooperative autonomy. The analysis reveals the transition from static empirical modelling toward hybrid physics, artificial intelligence (AI) frameworks capable of capturing nonlinear dynamics, uncertainty, and multi-vessel interactions. At the same time, this review highlights the growing influence of Convention on the International Regulations for Preventing Collisions at Sea (COLREGs), the Second-Generation Intact Stability Criteria, and emissions-reduction targets in shaping technical developments. While learning-enabled prediction, model predictive control (MPC)-based regulatory compliance, and real-time DT synchronisation show increasing maturity, this study identifies unresolved challenges, including domain shift, model interpretability, certification barriers, multi-agent safety guarantees, and DT divergence under sparse data. By mapping both demonstrated capabilities and conceptual frontiers, this review presents manoeuvring as a central pillar of future Maritime Autonomous Surface Ships (MASS) operations and sustainable shipping. The findings outline a research agenda toward integrated, explainable, and environmentally aligned manoeuvring intelligence that can support safe, efficient, and regulation-compliant autonomous maritime systems.

ORCID iDs

Tadros, Mina ORCID logoORCID: https://orcid.org/0000-0001-9065-3803, Aung, Myo Zin ORCID logoORCID: https://orcid.org/0000-0001-6370-0029, Louvros, Panagiotis ORCID logoORCID: https://orcid.org/0000-0001-8623-0680, Pollalis, Christos ORCID logoORCID: https://orcid.org/0000-0003-3264-4428, Nazemian, Amin ORCID logoORCID: https://orcid.org/0000-0001-6861-4488 and Boulougouris, Evangelos ORCID logoORCID: https://orcid.org/0000-0001-5730-007X;
CORE (COnnecting REpositories)