(03)

Science

↓ (W38 ‘26 · Sep 14–20)
01openalex2026-09-18Lu Liu, Yuan He, Xinwei Liu, Zhijian Sun +1 moreDOI ↗ (opens in a new tab)

Human-in-the-loop COLREGs-compliant platoon formation control of maritime autonomous surface ships via finite state machine (opens in a new tab)

This study presents a control system for maritime autonomous surface ships (MASSs) that integrates human supervision into platoon navigation while adhering to COLREGs collision avoidance rules. A virtual leader allows human operators to adjust the platoon’s speed, while a finite state machine identifies encounter scenarios and applies safety constraints via control barrier functions. The system uses a cooperative path-following guidance law and quadratic optimization to balance collision avoidance with platoon coordination. Simulations confirm the approach effectively maintains formation and complies with maritime safety regulations.

02openalex2026-09-17Yuhan Zhou, Huijin Xu, Maoyuan Sun, Shuai Huang +6 moreDOI ↗ (opens in a new tab)

Data-driven social-cognitive navigation for energy-efficient and low-carbon autonomous shipping (opens in a new tab)

This study introduces a Social-Cognitive Navigation Framework (SCNF) for autonomous shipping, using historical and real-time AIS data to enhance safety and efficiency. The framework combines a Recursive Hypergraph Transformer, Level-k reasoning, and a game-theoretic planner, outperforming existing methods in 500 trials. It achieved zero collisions, improved path efficiency, and reduced traffic disturbance in crossing and overtaking scenarios. While it suggests sustainability benefits, direct fuel and emissions reductions were not measured.

03crossref2026-09-15Qianfeng Jing, Xin Yang, Yong YinDOI ↗ (opens in a new tab)

Design and Implementation of a Ship–Shore Cooperative Experimental Platform for Unmanned Surface Vehicles (opens in a new tab)

This paper presents a ship–shore cooperative experimental platform for unmanned surface vehicles (USVs) to bridge the gap between simulation and real-world deployment. The system includes a shore control station, portable terminal, and onboard components with multimodal sensing, redundant communication (private radio, 4G/5G, and short-range RC), and hardware arbitration. A control-authority model ensures fail-safe transitions between autonomous and human control, while LiDAR-based obstacle detection enables collision avoidance. Field tests demonstrated autonomous navigation, human intervention, and data collection across 18.26 km of trajectories in four water environments.

04openalex2026-09-18Anastasiya GolovinaDOI ↗ (opens in a new tab)

Compliance with International Regulations for Preventing Collisions at Sea in the Context of the Introduction of Autonomous Shipping (opens in a new tab)

The study analyzes compliance with international collision prevention regulations, focusing on lights and signs, as autonomous shipping emerges. It highlights gaps in applying existing rules—designed for human-operated vessels—to autonomous ships, which rely on automated systems. The paper argues that autonomous vessels must meet equivalent safety standards and proposes legal and technical improvements to address enforcement challenges. Recommendations include adopting new technologies to ensure proper signaling on autonomous ships.

05crossref2026-09-17Ahmad Talha, Hafiz Muhammad Usama Hanif, Muhammad MustafaDOI ↗ (opens in a new tab)

The Role of AI and Autonomous Systems in Navigating China’s Future Maritime Sustainability and Blue Economy Governance (opens in a new tab)

This study explores how AI, blockchain, and IoT can improve efficiency and sustainability in China’s maritime sector and blue economy. It highlights challenges in governance, including cross-border data transfer and autonomous shipping, while stressing the need for updated laws. The paper provides policy recommendations for international cooperation and legal frameworks to support technological advancements. It also contributes to discussions on marine energy, environmental protection, and offshore industry regulations.

06openalex2026-09-19Gang Chen, Jianbo Zheng, Xinhao Zhao, Zihao Wang +3 moreDOI ↗ (opens in a new tab)

A transformer framework for vessel trajectory prediction in complex maritime scenarios with an original vessel trajectory dataset (opens in a new tab)

This paper introduces the Segmented Autoregressive Global Attention Mechanism Transformer (SAGM-TF) to improve multi-step vessel trajectory prediction for maritime collision avoidance. The framework combines an optimized kinematic encoding module, segmented autoregressive decoding, and a cross-segment global attention mechanism to reduce error accumulation over a 90-second horizon. A new trajectory dataset, incorporating heading angle and angular velocity, was created to better capture vessel maneuvering behavior. Experimental results show the method outperforms traditional approaches in accuracy and robustness for complex maritime scenarios.

07openalex2026-09-15Min Zhang, Fang Li, Sichao Chen, Hao WangDOI ↗ (opens in a new tab)

Pioneering a compound maritime legal ecosystem integrating "Legal AI" and "AI Law" (opens in a new tab)

The paper explores the emerging compound maritime legal ecosystem resulting from the Maritime Autonomous Surface Ship (MASS) Code, which governs both traditional and autonomous vessels. It highlights tensions between existing legal rules and AI governance, as well as challenges in establishing theoretical foundations for complex legal systems. The authors discuss the need for interconnected regulations to manage multi-level intelligent ships. The work focuses on integrating "Legal AI" and "AI Law" within this evolving framework.

08crossref2026-09-15Bo Wu, Zuyuan Liu, Jiajun Wang, Weihao Ma +1 moreDOI ↗ (opens in a new tab)

Energy–Time Co-Optimization for Autonomous Ship Berthing in Complex Ocean Currents Using an Improved hp-Pseudospectral Optimal Method (opens in a new tab)

This paper introduces an improved hp-pseudospectral (IHP) method for optimizing autonomous ship berthing paths in complex ocean currents. Unlike traditional methods, it avoids assuming constant surge velocity or thrust, enabling simultaneous optimization of speed and energy consumption. The IHP method divides time intervals, uses subdomain collocation, and transforms optimization to achieve Pareto-optimal paths. Simulations show it outperforms A* and genetic algorithms, reducing travel distance, sailing time, and energy consumption by up to 6.9%.

09crossref2026-09-14DymasDOI ↗ (opens in a new tab)

Pengembangan Autonomous Unmanned Surface Vehicle Nasional Untuk Pertahanan Maritim Dan Penanggulangan Bencana (opens in a new tab)

This study proposes developing a national autonomous unmanned surface vehicle (USV) for Indonesia to enhance maritime defense and disaster response. Current USV capabilities in Indonesia are limited to prototypes without sustainable operational integration. The research recommends creating an integrated system with modular platforms, control centers, and layered communications, supported by domestic industry and cross-agency collaboration. The goal is a versatile USV for surveillance, logistics, and search-and-rescue missions while maintaining human oversight.

10openalex2026-09-17Muhaidir Ikram, Josafat Gracia Ginting, Muh Nurfadel HamzahDOI ↗ (opens in a new tab)

The Role of Management in Developing Seafarers’ Digital Skills for Artificial Intelligence-Driven Maritime Transformation: A Systematic Literature Review (opens in a new tab)

This systematic review examines management's role in developing seafarers' digital skills for AI-driven maritime transformation. Key management responsibilities include governing competency standards, designing reskilling programs, leading organizational change, and ensuring operational readiness in safety and cybersecurity. The most critical competencies identified are digital literacy, AI and data literacy, cybersecurity, and cognitive-social skills like decision-making and communication. Challenges include outdated regulations, limited infrastructure, funding constraints, and gaps in training effectiveness, emphasizing the need for a coordinated framework among industry stakeholders.

11openalex2026-09-17Xiangkun Meng, Qinyu Fan, Wenjun Zhang, Xue YangDOI ↗ (opens in a new tab)

A cyber risk assessment framework for Maritime Autonomous Surface Ships integrating Dempster–Shafer evidence theory and rule-based Bayesian networks (opens in a new tab)

No abstract or body text was available, so this entry is reported from metadata only.

14openalex2026-09-17Mitja KovačDOI ↗ (opens in a new tab)

Maritime Shipping (opens in a new tab)

This paper explores the legal, economic, and regulatory effects of AI in maritime shipping. It outlines AI’s benefits for navigation, logistics, maintenance, and port operations but notes risks like data quality, cybersecurity, and liability issues. The study focuses on smart ports, autonomous vessels, and responsibility allocation among stakeholders in AI-related incidents. It proposes regulatory frameworks to support innovation while ensuring safety and legal clarity.

15openalex2026-09-15M. Yousaf, Aitor Arrieta, Shaukat Ali, Paolo Arcaini +1 moreDOI ↗ (opens in a new tab)

Search-Based Metamorphic Testing of Vision-Language Models in Autonomous Underwater Robotic Software (opens in a new tab)

This paper introduces MetaVLM, a search-based metamorphic testing method to evaluate vision-language models (VLMs) for autonomous underwater robots (AURs). The approach uses NSGA-II to apply minimal image transformations that expose VLM prediction failures, testing models like BLIP and CLIP against a random search baseline. Results highlight the strengths and weaknesses of these VLMs in underwater robotic software. The findings provide insights for improving quality assurance in VLM-based systems.

16crossref2026-09-14Douglas DeCandiaDOI ↗ (opens in a new tab)

Extending the Sensing Reach of Spacecraft with Autonomous Science Nodes (opens in a new tab)

The paper introduces Autonomous Science Nodes (ASNs), lightweight (~1 kg) microprobes deployed by a mothership to perform limited scientific measurements in extreme environments where conventional spacecraft struggle. These mechanically hardened nodes use spherical encapsulation, distributed loading, and high-energy deployment to survive harsh conditions. The study analyzes mass allocation, materials, power, communications, and redundancy, showing how ASNs enhance spatial coverage, resilience, and sampling capabilities. Applications demonstrate the flexibility of this architecture for extending mission reach beyond traditional spacecraft limitations.

19crossref2026-09-14Jarosław Szrek, Konrad Siudziński, Artur MuraszkowskiDOI ↗ (opens in a new tab)

A Terminal Navigation Approach for Autonomous Docking with Transport Trolleys Using Laser Scanning (opens in a new tab)

This paper introduces a cost-effective method for autonomous mobile robots to locate and dock with transport trolleys using a single LiDAR sensor. The system identifies trolley legs within predefined detection zones and enables docking without requiring precise robot positioning, utilizing an ESP32-based control system and ROS framework. Experiments confirmed successful trolley detection and docking when the robot was positioned in front of the target under controlled conditions. The approach aims to improve automated transport systems in warehouses and manufacturing facilities.

20openalex2026-09-18Churuo Zhang, Yan Zhang, Yang Liu, Jiahang LiDOI ↗ (opens in a new tab)

CEC-YOLO: a floating-debris detection algorithm for complex water-surface environments (opens in a new tab)

CEC-YOLO is a lightweight debris-detection algorithm based on YOLO11n, designed for complex water surfaces. It integrates existing feature-extraction and calibration modules in a task-specific structure, improving multi-scale debris representation while maintaining computational efficiency. The model achieved 88.9% mAP@0.50 at 175 frames per second on an RTX 3090, outperforming YOLO11n and other detectors in accuracy-speed balance. Validation on a public dataset confirmed its effectiveness beyond the self-built data, offering a deployable solution for water-cleaning vessels.

21openalex2026-09-15Natalia Dikul, Evgen Dykyi, Anastasiia Chyhareva, Svitlana Krakovska +1 moreDOI ↗ (opens in a new tab)

How Antarctic Ice and Southern Ocean Changes Are Interconnected with Climate, Sea Level, and Biodiversity (opens in a new tab)

This paper examines the link between Antarctic ice, the Southern Ocean, and broader climate, sea level, and biodiversity impacts. Researchers used a high-resolution atmospheric model to study how precipitation affects Antarctic ice shelf mass balance. Additional autonomous Argo floats were deployed to gather ocean data, improving knowledge of seasonal water exchanges between the Weddell Sea and the Antarctic Peninsula. The findings contribute to the OCEAN ICE project and address gaps in field observations.

22openalex2026-09-15Ran Ma, Kaiwen Zheng, Yingqian ZhangDOI ↗ (opens in a new tab)

Systemic immune programming in the life course of childhood asthma: a new perspective on monocyte pre-activation and trained immunity (opens in a new tab)

This paper introduces the "Systemic Priming and Homeostasis in Pediatric Asthma" (SPHPA) model, proposing that childhood asthma originates from early-life systemic immune reprogramming rather than just localized airway inflammation. Early environmental triggers, like viruses or allergens, induce trained immunity in hematopoietic stem cells, pre-activating monocytes before they reach the lungs. A key mechanism involves the LYN-SHIP-1-Trib1 signaling pathway, where SHIP-1 shifts from anti-inflammatory to pro-inflammatory, driving structural airway changes such as muscle thickening and cell overgrowth. The authors suggest future treatments should target systemic immune memory rather than just inflammation.

23openalex2026-09-13Jiahu Lei, Weiwei Bai, Yuanhao WangDOI ↗ (opens in a new tab)

Dynamic Event-Triggered Data-Driven Tracking Control for Under-Actuated Maritime Autonomous Surface Ships Using ADP (opens in a new tab)

This paper addresses optimal trajectory tracking for under-actuated Maritime Autonomous Surface Ships (MASS) with unknown dynamics using a dynamic event-triggered (DET) data-driven (DD) control approach. It employs identifier neural networks to estimate unknown ship dynamics from navigation data. The method aims to improve efficiency by triggering control updates only when necessary. The study proposes a solution for real-time tracking control in MASS systems.

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