(03)

Science

↓ (W29 ‘26 · Jul 13–19)
01openalex2026-07-15Sojin Kim, Jeonghong ParkDOI ↗ (opens in a new tab)

BIT* -based Path Planning for Remotely Operated Maritime Autonomous Surface Ships Under Dynamic Obstacle Uncertainty (opens in a new tab)

This paper introduces a BIT*-based path-planning method for Maritime Autonomous Surface Ships (MASS) to handle dynamic obstacle uncertainties in congested waters. The approach combines collision avoidance and path replanning into a single optimization problem, using probabilistic collision risk in the BIT* cost function to prioritize safer routes. It also integrates COLREGs rules to ensure compliance with maritime navigation regulations. Simulations show the method produces safe and reliable paths despite positional uncertainty from sensor errors and communication delays.

02crossref2026-07-17Marko Perkovič, Peter Vidmar, Blaž LuinDOI ↗ (opens in a new tab)

Smart Ports and Maritime Simulators in the Era of Maritime Autonomous Surface Ships (opens in a new tab)

The paper critiques the assumption that Maritime Autonomous Surface Ships (MASS) and port digitalization alone solve maritime transport challenges, arguing risks arise from systemic factors like vessel size, infrastructure limits, and organizational complexity. It emphasizes MASS as part of a broader socio-technical system, requiring smart ports, traffic management, and maritime simulators for safe coexistence with manned vessels. The role of simulators as cyber-physical test beds for validating operations, decision-support systems, and human-automation interaction is highlighted. The authors stress that successful MASS integration depends on managing complexity through predictive coordination, simulation-based validation, and regulatory adaptations, rather than just increasing autonomy.

03crossref2026-07-17Roberto TrevisaniDOI ↗ (opens in a new tab)

Resilient Sensing and Multi-Sensor Fusion for Autonomous Maritime Systems (opens in a new tab)

This paper explores how autonomous maritime systems depend on diverse sensors like radar, LiDAR, GNSS, and INS for navigation and surveillance. Challenges such as radar clutter, jamming, and GNSS signal interference threaten reliability, requiring techniques like clutter suppression and adaptive countermeasures. Multi-sensor fusion is highlighted as a solution to reduce uncertainty and improve situational awareness by combining data from complementary sensors. The approach ensures robust decision-making even in adverse or degraded conditions.

04crossref2026-07-17Levent KirvalDOI ↗ (opens in a new tab)

Maritime Economy and Autonomous Sea Navigation (opens in a new tab)

The maritime economy accounts for 80–90% of global trade by volume, making it critical to worldwide commerce. Autonomous navigation technologies, including Maritime Autonomous Surface Ships (MASS), are poised to transform vessel operations, port logistics, and supply chains. Advances in digitalization, AI, and autonomous systems are moving MASS from prototypes toward practical deployment. The paper examines economic drivers, technological progress, regulations, and future research in this evolving field.

05crossref2026-07-17Felix-Marcel PetermannDOI ↗ (opens in a new tab)

Human Factors Contributing to Remote Operation and Supervision of Autonomous Vessel Operations (opens in a new tab)

The paper examines human factors in remote supervision of autonomous vessels, highlighting that automation shifts rather than removes human roles, moving control from onboard crews to shore-based Remote Operation Centres (ROCs). Key challenges include reduced sensory cues, vigilance decline, situation awareness gaps, mode confusion, and delayed intervention during emergencies. Using a maritime failure case, the study proposes design guidelines to improve remote operation resilience, demonstrated through tools like the Maritime Head-Up Display (mHUD) and Digital Fire Central (DFC). Effective remote operations depend on interfaces and feedback systems aligned with human cognitive and perceptual needs.

06openalex2026-07-14Komitov D.DOI ↗ (opens in a new tab)

OPERATIONAL CHALLENGES OF AUTONOMOUS MARITIME NAVIGATION UNDER EXTREME AND ABNORMAL CONDITIONS (opens in a new tab)

Autonomous ships use algorithms, sensors, and AI for navigation, reducing human roles to remote supervision. This shift aims to improve efficiency, safety, and sustainability in maritime transport. However, it requires strict regulations to protect lives, cargo, and vessels. The paper explores AI-driven navigation, course correction, and challenges in safety and legal frameworks.

07crossref2026-07-17Murat Selçuk SolmazDOI ↗ (opens in a new tab)

Collision Liability for Autonomous Vessels (opens in a new tab)

The paper examines legal challenges arising from collisions involving autonomous vessels, or Maritime Autonomous Surface Ships (MASS), as their use grows alongside manned ships. The International Maritime Organization (IMO) has defined MASS and categorized their autonomy levels, but liability rules for collisions remain unclear. The study analyzes potential liability issues and proposes recommendations to establish a legal framework for such incidents. Current regulations only address collisions between manned vessels, leaving gaps for autonomous vessel scenarios.

08crossref2026-07-17Pasquale Daponte, Luca De Vito, Sergio RapuanoDOI ↗ (opens in a new tab)

Sensors for Maritime Autonomous Surface Systems Navigation (opens in a new tab)

This paper reviews key sensor technologies used in Maritime Autonomous Surface Systems, explaining their functions and integration within autonomous navigation. It emphasizes the importance of sensor data fusion to improve environmental awareness. The authors discuss recent advancements and future trends, particularly quantum inertial and magnetic sensors, which are expected to transform navigation technology. The focus is on their potential impact in the coming years.

09openalex2026-07-14Khairul Izzati bin Kamarumtham, Koji MuraiDOI ↗ (opens in a new tab)

Quantitative Gaze Similarity Analysis for Operation-based Maritime Studies: A Conceptual Approach (opens in a new tab)

This paper introduces a quantitative method for analyzing gaze similarity in maritime operations to assess perceptual performance and situational awareness. The approach eliminates subjective judgment, improving accuracy and reproducibility in experimental settings. An experiment using simulated remote ship operations demonstrated the method’s feasibility by analyzing fixation data from navigational scenarios. The results suggest it can complement existing frameworks for evaluating maritime professionals' perceptual skills.

10crossref2026-07-14Iryna ShvetsovaDOI ↗ (opens in a new tab)

XR-Enhanced Maritime English Training for Digital Navigation (opens in a new tab)

This study explores the use of Extended Reality (XR) and AI feedback tools in Maritime English training to improve communication in digital navigation. It introduces an XR-based instructional model to enhance cadets' procedural fluency, clarity, and stress-resilient communication, aligning with IMO SMCP standards. Results show XR environments boost terminological accuracy, fluency, and responsiveness in emergencies and team tasks. Cadets also reported greater confidence and reduced hesitation under operational pressure.

11openalex2026-07-13Yangyang Liu, Tianyu Li, Yuan Zhao, Chengkai Tang +2 moreDOI ↗ (opens in a new tab)

Anti-interference multi-scale detection algorithm for unmanned surface vehicles based on dynamic feature enhancement (opens in a new tab)

The paper introduces YOLO-MKV, an object detection algorithm for unmanned surface vehicles (USVs) designed to improve accuracy in complex marine environments. It combines a Multi-Scale Adaptive Kernel Convolution (MSAK) module with a Mixed Local-Channel Attention (MLCA) mechanism to enhance multi-scale feature extraction while maintaining low computational cost. The algorithm also integrates a high-resolution detection head and a Vision Transformer module, alongside a dynamic focusing mechanism using WIoU v3 loss to refine bounding box precision. Tests on the WSODD dataset show YOLO-MKV outperforms baseline models, achieving 82.0% mAP@0.5 and 47.3% mAP@0.5:0.95 with minimal parameters (2.67M) and computational demand (11.0 GFLOPs).

12crossref2026-07-15Ling Qin, AnChuan Wang, Qing Huang, Qun ZouDOI ↗ (opens in a new tab)

Frequency-Guided Real-Time Detection of Weak Water-Surface Targetsfor Unmanned Surface Vehicles (opens in a new tab)

This paper introduces a lightweight detector for unmanned surface vehicles to identify weak water-surface targets in real time. It uses frequency analysis to enhance features, focusing on mid-frequency energy unique to water-surface imagery, and employs adaptive localization supervision to improve detection accuracy. Tests on FloW and PoTATO datasets show improved performance in detecting small targets while maintaining real-time speed. Future work includes embedded deployment and more rigorous evaluation.

15crossref2026-07-17Thanos PanagopoulosDOI ↗ (opens in a new tab)

The Rise of Autonomous/Intelligent Production (Toward Maturity) (opens in a new tab)

This paper explores autonomous production as a major shift in labor, technology, and societal structures. Authored by Thanos Panagopoulos in 2026, it analyzes its development toward maturity. The chapter focuses on its implications without detailing specific methods or outcomes. No additional claims beyond its transformative potential are presented.

16openalex2026-07-13R Ferreira da Silva, Milad Abolhasani, Peter Beaucage, Laura Biven +24 more

Toward Trustworthy Autonomous Science: A Two-Year Community Roadmap (opens in a new tab)

The paper updates a 2025 roadmap for autonomous science, noting rapid progress in multi-agent systems, interoperable labs, and AI models, alongside setbacks like retracted discoveries and flawed benchmarks. It highlights a shift in challenges—from generating discoveries to verifying them—as the field’s key limitation. The revised roadmap expands to seven dimensions, elevating trust, verification, and governance as priorities, and introduces four new milestones. The next two years focus on standardization, verification frameworks, and federated, secure coordination across global and commercial platforms.

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