(03)

Science

↓ (W32 ‘26 · Aug 3–9)
01openalex2026-08-04Xinyue Nian, Deling Wang, Xinqiang ChenDOI ↗ (opens in a new tab)

Risk Evaluation of Maritime Autonomous Surface Ship Operations: A Formal Safety Assessment Approach (opens in a new tab)

This paper introduces a Formal Safety Assessment (FSA) framework to evaluate risks in Maritime Autonomous Surface Ship (MASS) operations, addressing gaps in traditional methods that rely on crewed-ship data. It establishes a hierarchical risk indicator system across five dimensions—ship machinery, human factors, environment, information technology, and management—using frequency and severity indices to classify risks. A case study with 50 experts found MASS operations fall within the "ALARP" (tolerable) risk region, with environmental, IT, and machinery factors posing the highest risks. Key contributors to overall risk include environmental perception, navigation decision-making, and communication capability.

02openalex2026-08-07Arthur C. TrembanisDOI ↗ (opens in a new tab)

Autonomous Exploration and Digital Documentation of Great Lakes Shipwrecks: A Multi-Platform Survey Framework for Maritime Heritage (opens in a new tab)

This study introduces a multi-platform autonomous survey framework for documenting Great Lakes shipwrecks, tested in Lake Michigan and Lake Ontario (2021–2022). The approach combines AUVs, ASVs, sonar, magnetometry, and optical imaging in a structured workflow to cover large areas efficiently. Surveys generated 19.72 km² of geophysical data, including sonar mosaics and magnetic maps, leading to the discovery of a previously unknown wooden shipwreck in Lake Ontario. The method improves efficiency, adaptability, and scalability for preserving submerged cultural heritage.

03openalex2026-08-06Tiancheng Li, Anna Soh, Bernard Voon Ee HowDOI ↗ (opens in a new tab)

AI-Driven Mooring Control for Autonomous Engineering Vessels (opens in a new tab)

This paper explores an AI-driven mooring control system for autonomous engineering vessels, replacing manual winch adjustments with an adaptive neural feedback law. The method compensates for unknown vessel dynamics and environmental disturbances in real-time without prior model identification. Simulations show the neural controller achieves steady-state positioning accuracy comparable to model-based designs, while a reinforcement learning (PPO) approach performs similarly to a PD regulator but with less precision. The system is proven stable (SGUUB) and respects physical constraints like line tension limits.

04openalex2026-08-05Xin Xiong, Rudy R. Negenborn, Yusong PangDOI ↗ (opens in a new tab)

Hydrodynamics-aware formation control for energy-efficient multi-vessel systems: A review (opens in a new tab)

This review analyzes 193 studies on hydrodynamics-aware formation control for energy-efficient multi-vessel systems, highlighting the challenge of integrating hydrodynamic resistance reduction into real-time control. It categorizes research into five evidence levels, comparing models like CFD, potential-flow, and surrogates for real-time use, differentiability, and compatibility with model predictive control (MPC). While evidence from CFD and experiments exists, closed-loop validation addressing hydrodynamics, energy metrics, and real-world constraints remains limited. Key priorities include developing control-ready hydrodynamic models, propulsion-aware energy accounting, and field validation for practical deployment.

05openalex2026-08-03Arati Uday KamatDOI ↗ (opens in a new tab)

Hour-Aware Adaptive Risk Management for Autonomous Memecoin Trading: Companion Dataset + Manuscript Bundle (opens in a new tab)

This paper presents a dataset and manuscript bundle for an autonomous memecoin trading system tested on Solana decentralized exchanges over 15 days. The dataset includes 190 closed paper-trades, 4,874 post-rejection price samples, and supporting figures, alongside a corrected version of the manuscript (v4). The research addresses hour-aware risk management and was revised in response to editorial feedback for resubmission to *Ledger*. The bundle is licensed under CC-BY-4.0, with a pending patent related to the trading system.

06openalex2026-08-03Nicholas J. Nidzieko, Paige HoelDOI ↗ (opens in a new tab)

Autonomous quantification of kelp biomass on offshore aquaculture installations using side scan sonar (opens in a new tab)

This study introduces a method using side scan sonar (SSS) to autonomously quantify kelp biomass on offshore aquaculture farms. The approach applies geometric principles to estimate kelp height and standing biomass, validated with in-situ measurements at a commercial kelp farm near Santa Barbara, California. The technique aims to reduce the time, labor, and cost of traditional monitoring while supporting large-scale kelp farming. It offers a scalable solution for assessing infrastructure and crop growth amid rising global demand for macroalgae.

08openalex2026-08-03Mustafa Wassef Hasan, Nizar Hadi AbbasDOI ↗ (opens in a new tab)

Disturbance-observer-based adaptive neuro-fuzzy sliding mode control for collaborative ASV and URV systems (opens in a new tab)

This paper introduces a control framework (DO-ANFSMC) for collaborative autonomous surface (ASV) and underwater (URV) vehicles in search-and-rescue missions, addressing environmental disturbances and obstacle avoidance. The method combines adaptive neuro-fuzzy systems, disturbance observers, and sliding-mode control, with parameters optimized via an improved grey wolf optimizer (IGWO-CT). Simulations with one ASV and two URVs demonstrated low yaw-rate tracking errors (0.00185–0.01915 rad/s) and reduced path lengths (68.171–79.399 m) while ensuring obstacle clearance. Results show improved trajectory tracking, disturbance rejection, and navigation efficiency compared to alternative approaches.

09openalex2026-08-06Rui Sun, Lvzhen Ren, Wen Ma, Zeng LulingDOI ↗ (opens in a new tab)

Research on the vessel passing capacity of the Changshan waterway (opens in a new tab)

This study evaluates the vessel passing capacity of the Changshan Waterway, a critical route between the Bohai and Yellow Seas. Using AIS data and a simulation model in AnyLogic, researchers estimate the waterway’s annual throughput capacity at 248,000 vessels. Current usage is at 66.4% saturation, nearing operational limits. The paper suggests speed regulation and spacing adjustments to improve capacity.

10openalex2026-08-06Yuxin Li, Xun Wu, Xin Liu, Zejian Zhang +2 moreDOI ↗ (opens in a new tab)

Frequency-aware high-precision formation control of unmanned surface vehicle clusters (opens in a new tab)

This paper introduces a frequency-aware formation control method for unmanned surface vehicle (USV) clusters to address challenges like environmental disturbances, noisy measurements, and actuator limitations. The approach combines command-filtered backstepping, sliding-mode control, a saturation-protected high-gain observer, and momentum-based disturbance estimation to mitigate phase lag, observer peaking, and communication issues. The framework ensures bounded tracking errors and stability through Lyapunov-based analysis. Simulations confirm the method's effectiveness and improved performance.

12openalex2026-08-03Elizabeth Dietrich, Hanna Krasowski, Emir Cem Gezer, Roger Skjetne +2 more

Staying on Spec: Real-Time Monitoring under Uncertainty with a Maritime Case Study (opens in a new tab)

This paper introduces a real-time monitoring framework for robotic systems operating under uncertainty, reducing data needs by using data-driven reachable sets to evaluate task and safety specifications. The approach is applied to maritime navigation, addressing complex traffic rule requirements with a data-efficient method for constructing reachable sets. The framework is validated through simulations and hardware tests, showing improved risk detection over existing metrics under realistic conditions. The work focuses on real-time deployment and robustness to disturbances.

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