← (Macro-trends)Safety, risk & verification
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This study enhances the ship domain model using an N-focal ellipse to improve risk assessment for maritime autonomous surface ships (MASS). It distinguishes between collision-avoidance tasks involving moving objects under COLREGs and other navigational hazards by categorizing foci into vessel dimensions, kinematic parameters, and maneuvering characteristics. The model introduces multipliers to adjust domain boundaries based on navigation conditions and defines a minimum navigational safety margin. Simulations support the findings, suggesting the model could advance MASS navigational safety when integrated into control systems.
This paper reviews ship path planning for autonomous navigation, highlighting its complexity due to collision risks, efficiency, COLREGs compliance, and environmental factors. It compares model-driven methods (search-based, optimization) with deep reinforcement learning approaches, focusing on decision-making, safety, and multi-vessel interactions. Key challenges include rule formalization, partial observability, benchmark inconsistencies, and limited real-world validation. Future priorities involve safety constraints, digital twins, meta-learning, and scalable multi-agent coordination for reliable deployment.
This paper addresses gaps in the International Regulations for Preventing Collisions at Sea (COLREG) for Maritime Autonomous Surface Ships (MASS) by incorporating relative speed variations between vessels, expanding on prior work limited to identical-speed scenarios. It adapts collision-risk geometry calculations, such as collision angle, to assess how speed differences affect navigation safety. The study refines a geometric optimization method to efficiently analyze two-dimensional encounter scenarios, maintaining near-polynomial search complexity. The approach identifies high-risk vessel positions in under half a second, making it viable for onboard navigation warning systems.
This paper analyzes how remotely operated Maritime Autonomous Surface Ships (MASS) without crew redistribute environmental protection duties among ship systems, Remote Operations Centres (ROCs), and external support. It assesses whether existing pollution prevention, reporting, and emergency response functions can be maintained at equivalent levels under UNCLOS and IMO frameworks. The authors argue that coastal states’ jurisdiction should not expand beyond current limits, with pre-incident regulations and post-incident enforcement requiring clear legal boundaries. The study emphasizes clarifying how existing environmental protections apply to MASS rather than creating new regulatory powers.
This study examines how Maritime Autonomous Surface Ships (MASS) interact with crewed vessels, focusing on the challenges faced by conventional Officers of the Watch (OOW) during collision avoidance. It introduces a framework analyzing situational awareness, mental models, and decision-making in mixed-traffic scenarios. Key issues include communication gaps, uncertainty about MASS capabilities, and trust in autonomous systems. The paper proposes using Full Mission Bridge Simulators to study OOW behavior and decision-making in these encounters.
This paper presents a modernized three-level hierarchical control system for Maritime Autonomous Surface Ships (MASS) to handle external disturbances like waves, wind, and currents. It proposes a modified proportional-derivative control law with corrections for roll, trim, and feedforward compensation, improving course accuracy and reliability in harsh conditions. The system integrates sensor data, processing, and control levels while monitoring seakeeping parameters without extra sensors. Its scalable and open structure allows integration with vessel traffic and motion control systems, enhancing navigation safety.
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.
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.
The paper introduces a generative AI framework that converts real-world ship trajectories from AIS data into realistic safety-critical encounter scenarios for testing autonomous maritime navigation systems. It uses a multi-scale temporal variational autoencoder to improve trajectory realism and robustness, even with noisy AIS data. The method enables scalable generation of diverse high-risk scenarios beyond historical records, supporting digital testing and safety assessments. Code for the framework is publicly available.
This paper reviews the evolution and current state of ship route planning algorithms for Maritime Autonomous Surface Ships (MASS), highlighting human error as a key cause of maritime accidents. It categorizes algorithms into three groups: baseline trajectory methods, environment-adaptive methods, and multi-objective intelligent decision-making methods, analyzing their applications, limitations, and COLREGs compliance. The study identifies gaps in existing algorithms, suggesting future trends include integrating multiple approaches, interdisciplinary collaboration, and addressing uncertainty. Refining COLREGs integration is noted as critical for advancing autonomous shipping and global trade.
The paper introduces a High-Frequency Composite Safety Index (HF-CSI) for real-time risk assessment of Maritime Autonomous Surface Ships (MASSs), combining weather, collision, machinery health, and grounding risks into a single 0–10 scale. Using full-scale voyage data from a container ship over 6.5 days, the HF-CSI averaged 8.01, with dominant risks varying by sea area and no single hazard accounting for over 65% of risk-bearing samples. A non-compensatory weighted-maximum rule prevents critical hazards from being masked, and the method accurately flagged high-risk segments that compensatory averaging missed. The framework also differentiates collision avoidance behaviors and adjusts machinery health baselines based on propulsion modes.
This study introduces an energy field model for assessing navigation risks in Maritime Autonomous Surface Ships (MASS), focusing on multi-ship interactions. It quantifies maritime traffic complexity using ship attributes and the Potential Risk Ship Domain (PRSD) framework, then develops a model to capture dynamic interactions between ships. The approach classifies navigation scenarios using the ALARP principle, enabling adaptive operation mode switching. Results show the model effectively identifies risk patterns in high-density traffic, improving MASS safety in complex environments.
The paper examines regulatory gaps in classifying high-impact AI for Maritime Autonomous Surface Ships (MASS), noting that the EU’s AI Act (2024) and South Korea’s AI Framework Act (2025) lack specific criteria for autonomous shipping. It proposes five criteria—navigation centrality, reliability under stress, systemic harm potential, data integrity dependence, and lack of human override—to define high-impact AI in this context. The authors link accurate classification to supply chain resilience, maritime safety, and environmental protection, given the sector’s critical role in global trade. The rapid adoption of MASS has outpaced existing governance frameworks, raising concerns about safety and regulatory legitimacy.
VesselNav-Bench is an open benchmark for comparing autonomous ship navigation policies, using a shared 3-DOF simulator to ensure transparent and reproducible evaluations. Seven agents, including rule-based, optimization-based, and learning-based methods, were tested across nine scenarios under calm and disturbed conditions, with 360 episodes per agent. Classical and MPC approaches performed best in calm conditions, while MPC excelled under disturbances; safety shielding improved RL policy safety but revealed persistent generalization gaps. COLREGS Rule 17 compliance was limited to 0.76 across all agents, highlighting challenges for ASV certification. The benchmark, including code and logs, is publicly available.
This study introduces an LLM-based framework to analyze Remote Operation Centres (ROCs) for Maritime Autonomous Surface Ships (MASS) using patent data. It identifies 22 key technology domains, with maritime data communication, remote control, and teleoperation as the most interconnected clusters. The analysis of 973 patents shows rapid growth in ROC technologies post-2018, driven by advancements in sensing, communication, and control systems. Findings highlight the need for standardized safety measures and targeted investments to support reliable MASS operations.
This paper presents a combined risk assessment framework for Maritime Autonomous Surface Ships (MASS) that merges System-Theoretic Process Analysis (STPA) and Fault Tree Analysis (FTA). The approach runs both methods in parallel within a shared system architecture to link hazards, unsafe actions, and failure events. A case study of a semi-autonomous freight vessel in the North Sea highlights risks like perception errors, communication failures, and collision misjudgments. The framework aims to improve safety assessments by connecting systemic control issues to accident pathways.
17Offshore Energy2026-10-20
The OceanAlpha L42B, an uncrewed marine survey surface vessel (USV), received an Approval in Principle (AiP) certificate from Bureau Veritas. This certification acknowledges the vessel's compliance with preliminary design and safety standards. The L42B is designed for marine survey applications. The approval marks a step toward its operational deployment.
This study introduces a data-driven framework to improve collision-risk assessment for autonomous ships by combining Bayesian risk modeling with system identification-based manoeuvring predictions. It analyzes global maritime accident data using Bayesian Networks to identify key risk factors, then applies Dynamic Bayesian Networks to predict real-time collision risks during ship encounters using AIS data. The research also develops a non-parametric model to predict ship manoeuvring behavior, validated with KCS benchmark ship data, achieving accuracy comparable to deep learning with lower computational costs. The findings support enhanced collision risk evaluation and autonomous navigation through realistic trajectory predictions and control strategies.
This study applies complex spherical fuzzy failure mode, effects, and criticality analysis (FMECA) to assess risks in Maritime Autonomous Surface Ships (MASS). The method integrates fuzzy sets to handle uncertainty and interconnected failures in autonomous maritime systems. Expert evaluations, combined using fuzzy aggregation, determined severity, occurrence, and detectability of failure modes, producing a risk priority number (RPN). The highest RPN was assigned to the human-machine interface (HMI), identifying it as the most critical failure mode for MASS operations.
This study introduces a fractal–episodic framework to analyze ship-control microvariability for navigation risk monitoring in Maritime Autonomous Surface Ships (MASS). The method processes AIS/ECDIS trajectory data using sliding-window analysis, fractal measures (Higuchi, DFA, Katz), and weighted aggregation to generate a chaos score and confidence index. It converts micro-motion irregularities into interpretable passage-level indicators for human-factor-aware risk assessment. The approach aims to enhance decision-support systems in autonomous maritime operations.
This paper examines the limitations of current autopilot systems in autonomous ships, which mainly handle basic navigation and lack strong collision avoidance. It proposes using VR simulators and model-scale vessel testing as a controlled "sandbox" environment to improve autonomous navigation. The study highlights the role of advanced predictors and AI in detecting and preventing close-encounter situations early. It also stresses the need to ensure both hardware and software reliability in AI systems to handle potential failures and maintain safety.
The paper examines the duty to rescue at sea in relation to Maritime Autonomous Surface Ships (MASS), arguing that autonomy does not exempt vessels from rescue obligations. It analyzes how the IMO MASS Code’s Chapter 21 translates this duty into a goal-based framework, aligning with SOLAS requirements. Flag states must enforce compliance through certification and oversight, while coastal states must integrate MASS into search and rescue (SAR) coordination and ensure survivor disembarkation. The study outlines responsibilities for both flag and coastal states to ensure MASS can effectively assist persons in distress.
The paper examines legal uncertainties surrounding Maritime Autonomous Surface Ships (MASS) under current international maritime law, which remains human-centered. It highlights gaps in regulations due to AI-driven operations that separate control from the physical vessel. The study proposes redefining the captain’s role, the ship’s legal status, and shifting liability from fault-based to strict or product liability. It also recommends restructuring responsibilities from individuals to systems to improve legal predictability and flag state oversight.
This study introduces a framework for improving the safety of maritime autonomous surface ships (MASS) by analyzing perception uncertainty and optimizing sensor layouts. It models sensor detection probabilities, state-estimation uncertainties, and collision risks using an ellipse-based safety envelope. The optimized sensor configuration achieved 68.49% mean coverage, outperforming a fixed heuristic layout (67.89%), with daytime and nighttime coverage of 74.45% and 62.56%, respectively. A synthetic scenario with ten ships demonstrated the framework’s effectiveness in evaluating sensor performance under SOTIF constraints.
This paper presents a model-based method to automatically generate assurance scenarios for verifying COLREGS compliance in autonomous surface vehicles (ASVs). It derives functional equivalence classes for multi-vessel encounters, maps them to logical scenarios with geometric constraints, and produces initial scenes using search-based and rejection sampling algorithms. The approach ensures full coverage of COLREGS-relevant encounters and scales to scenarios involving up to six vessels. Evaluation confirms its effectiveness for ASV assurance in open-sea conditions.
The paper examines maritime autonomous surface ships (MASS) from the perspective of seafarers, focusing on operational, spatial, and labour impacts. Interviews with maritime professionals reveal tensions between automation and manual tasks, challenges in complex coastal areas, and mixed views on the future of maritime jobs. Findings suggest MASS will redefine rather than eliminate human labour, requiring regulatory, training, and infrastructure adjustments. The study advocates for a human-centric transition framework that accounts for spatial differences and occupational expertise.
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.
This study uses the SHELL model (Software, Hardware, Environment, Liveware) to create a human-focused framework for Maritime Autonomous Surface Ships (MASS). It examines how humans interact with AI-driven systems, considering regulatory software, system hardware, environmental factors, and human roles. The framework aims to improve safety and reliability by addressing key challenges in human-machine integration. It provides a foundation for future research on complex MASS operations.
This paper examines the legal challenges posed by autonomous ships under EU AI liability frameworks. It highlights the shift from strict liability in maritime conventions to a fault-based approach in the EU’s 2022 AI Liability Directive and 2024 AI Act, which aims to ease victims' evidentiary burdens. The authors argue that preserving the shipowner’s central role in liability rules, as in traditional maritime law, ensures fair risk distribution and effective compensation. The study contrasts EU developments with existing maritime conventions like CLC 1992 and Bunkers 2001.
30remio.ai2026-11-02
Singapore issued a warning on October 29, 2026, highlighting maritime security risks posed by AI and autonomous ships, while still supporting their adoption. Law Minister Edwin Tong, speaking at the UN Security Council, emphasized the need for accountability, transparency, and human oversight to counter threats like cyberattacks and unlawful vessel control. The statement aligns with Singapore’s push for autonomous shipping innovation but stresses safeguards under international law, including the UN Convention on the Law of the Sea. The country is advancing autonomous feeder operations for container logistics, requiring proposals to address cybersecurity, redundancy, and regulatory compliance.
31Smart Maritime Network2026-11-02
Singapore highlighted security risks and opportunities posed by AI and autonomous ships in the maritime sector during a UN Security Council address. The country, alongside Fiji, Jamaica, and Malta, emphasized the need for international safeguards to balance technological advancements with safety and security. While supporting the IMO’s non-mandatory MASS Code, Singapore called for a mandatory framework to regulate autonomous vessels and prevent misuse, such as cyber-attacks or interference with shipping. The statement stressed the importance of accountability, transparency, and human oversight in AI systems to uphold maritime safety and international law.
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.
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.
34Splash2472026-11-02
The NTSB recommended new U.S. safety standards for uncrewed vessels after a 2024 collision in Lake Erie between a NOAA autonomous research craft and a recreational yacht. The low visibility and passive remote monitoring of the uncrewed vessel contributed to the incident, causing significant damage and minor injuries. Investigators found no existing industry-wide regulations for detectability, collision avoidance, or navigational safety of such vessels. The NTSB urged the U.S. Coast Guard to create a national regulatory framework to address these gaps.
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.
This paper examines safety challenges in maritime autonomous surface systems, highlighting risks from degraded communication, unclear control authority, and delayed human intervention. It analyzes 80 documented hazard scenarios from regulations, trials, and incident reports to identify key risk areas like remote supervision, control links, and navigation interactions. The study proposes a safety engineering approach to define control constraints and recovery requirements, emphasizing the need for explicit degraded modes, fallback behaviors, and emergency coordination. Findings show safety depends more on system design and recovery protocols than autonomy level alone.
The study introduces a bilateral negotiation model to enable autonomous and conventional ships to coordinate collision avoidance in mixed navigation scenarios. Using the Zeuthen strategy for bargaining and unilateral Bayesian learning for information estimation, the method improves negotiation efficiency with minimal data exchange from conventional ships. Simulation results show it resolves uncoordinated encounters, reduces unnecessary evasive maneuvers by autonomous ships, and enhances navigational safety. The approach addresses gaps in collaborative collision avoidance for heterogeneous fleets.
This paper introduces a framework to identify and prioritize critical safety factors during transitions between manual and autonomous navigation in marine vessels. Using System-Theoretic Process Analysis (STPA), the authors analyze hazards, model control structures, and pinpoint unsafe actions like delayed transitions or alarm failures. The method was applied to an autopilot system between two ports, leveraging maritime incident reports to uncover risks. Findings aim to guide safety improvements for Maritime Autonomous Surface Ships (MASS) in mixed fleets.
39Business Wire2026-11-05Naval News
Fairbanks Morse Defense introduced AutoHook, a system for fully autonomous vessel recovery, at EURONAVAL 2026. The technology aims to enable unmanned ships to perform recovery operations without human intervention. The unveiling took place on November 5, 2026. No specific technical details or performance results were disclosed in the announcement.
40oceannews2026-11-02
Fairbanks Morse Defense unveiled AutoHook™ at EURONAVAL 2026, a fully autonomous vessel recovery system for uncrewed surface vessels (USVs) developed by Vestdavit. The system operates without human intervention, achieving reliable performance in Sea State 4 conditions—surpassing current solutions limited to Sea State 2. AutoHook eliminates manual connections, reducing injury risks, and integrates easily with existing vessels due to its compact, clamp-on design. Designed for NATO-aligned interoperability, it supports allied fleets with real-time tracking and autonomous recovery in high-risk maritime environments.
This study introduces a method to identify high-risk ships in mixed maritime traffic involving autonomous (MASS) and conventional vessels. It uses a 4D-OPTICS approach to filter ships in dense encounters and an Axiomatic Fuzzy Set (AFS) model to convert risk indicators into interpretable semantic categories like spatial proximity and motion uncertainty. A hierarchical model then prioritizes ships based on COLREGs rules and semantic risk levels. Simulations and real-world AIS data from Yingkou Port validate the framework’s effectiveness.
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.
43The Texan2026-06-19
A Texas-based autonomous surface vessel assisted in rescuing helicopter pilots in the Strait of Hormuz in June 2026. The unmanned vessel played a role in the operation, though specific details of its involvement were not disclosed. The incident highlights the growing use of autonomous technology in maritime rescue missions. No further information about the pilots or the cause of the incident was provided.
This paper provides frozen reproduction materials for a synthetic study on mixed autonomous and human-driven ship traffic. It includes code, numerical data, reference scenarios, and instructions for independent verification. The results are not based on real-world AIS or maritime traffic data and should not be considered certified for navigation safety. The archive uses open licenses (Apache-2.0, CC BY 4.0) for author-owned content, with upstream MIT/BSD terms for third-party software, and restricts checkpoint deserialization to trusted local files.
This study analyzes safety risks in semi-autonomous navigation ships using System-Theoretic Process Analysis (STPA) to model interactions in encounter scenarios and identify potential hazards. To strengthen human factors analysis, the Cognitive Reliability and Error Analysis Method (CREAM) is integrated with STPA. The combined STPA-CREAM approach provides targeted recommendations to enhance the safety of semi-autonomous navigation systems. The research focuses on improving navigation efficiency while addressing risks in intelligent ship operations.
The paper explores conflicts between the **LLMC** (Convention on Limitation of Liability for Maritime Claims) and **EU Directive 2024/2853**, which extends product liability to software in autonomous ships. Directive 2024/2853 imposes strict liability for defective products and prohibits limitation in such cases, potentially overriding the LLMC’s liability caps. Shipowners may be classified as "economic operators" under the Directive, exposing them to unlimited liability for navigation system failures. The analysis concludes that EU law’s primacy may restrict the LLMC’s application in product defect claims, reshaping maritime liability for autonomous vessels.
The paper examines regulatory challenges posed by Maritime Autonomous Surface Ships (MASS) at the international level. Key issues include adapting MASS to the law of the sea, particularly regarding passage rights and flag state responsibilities. Technical regulation is progressing through the draft MASS Code, though gaps remain in areas like collision avoidance (COLREGs) and watchkeeping. The shift from human-operated to autonomous vessels also raises unresolved questions about civil liability for damages.
48NavalToday.com2026-04-23
Leonardo has installed a counter-unmanned aerial system (UAS) on an autonomous unmanned surface vessel. The integration aims to enhance maritime security by detecting and neutralizing drone threats. This development was reported by NavalToday.com on April 23, 2026. No further technical or operational details were provided.
49ASDNews2026-11-02
STARK unveiled Vanta 24, a 24-meter autonomous vessel designed for the Baltic Sea to counter threats like foreign warships, submarines, and shadow fleet tankers. Equipped with anti-ship missiles, a 30 mm gun, and long-range radar, it operates in harsh conditions and can escort warships or guard underwater infrastructure independently. The vessel supports NATO’s hybrid navy concept, offering scalable, cost-effective maritime defense with minimal crew requirements. Vanta 24 is part of STARK’s expanding autonomous fleet, controllable via Minerva software alongside smaller vessels.
This study introduces an MBSE-based method to define, quantify, and verify operational design domains (ODDs) for autonomous ship functions. It converts regulatory, mission, and risk requirements into measurable ODD conditions, ensuring traceability across system architecture, verification scenarios, and runtime logic. The approach is demonstrated through a collision-avoidance case study, where ODD conditions are formalized and tested via model checking, simulations, and risk analysis. Results confirm consistency in model-level verification but do not validate real-world operational safety or threshold effectiveness.
51Black Enterprise2026-08-04
Autonomous ships are transforming maritime safety by reducing human error, a leading cause of accidents at sea. These vessels use advanced sensors, AI, and real-time data to navigate and avoid collisions. The technology aims to improve efficiency and reliability in shipping operations. Industry experts predict widespread adoption in the coming years.
This study introduces a framework for creating realistic collision-avoidance testing scenarios for autonomous ships by analyzing actual collision cases. The framework involves collecting collision data, extracting ship trajectories, and developing diverse encounter situations by adjusting ship roles and positions. The resulting scenarios reflect real-world complexities, such as rule violations, dynamic encounters, speed changes, and environmental factors. These scenarios aim to improve the validation of collision-avoidance algorithms and enhance maritime safety.
This paper examines updates needed for the International Regulations for Preventing Collisions at Sea (COLREGS) due to advancements like larger and faster ships, new navigation technologies, and autonomous vessels. It proposes methods to interpret COLREGS, including defining danger zones and determining timely actions for ships. The authors critique existing rules, suggest amendments, and emphasize classifying vessel approach situations. The study also addresses incorporating regulations for Maritime Autonomous Surface Ships (MASS) into COLREGS.
This study reviews system-theoretic safety approaches (STAMP, STPA, CAST) in the maritime sector using a hybrid methodology combining PRISMA, bibliometrics, and scoping. STPA is identified as the dominant method, particularly for Maritime Autonomous Surface Ships (MASS) and remote operations. Key gaps include limited validation, inconsistent loss scenario treatment, and weak integration of human and organizational factors. The review of 76 papers (2015–2024) highlights STPA’s growing use and its integration with quantitative methods like QRA.
55Janes2026-10-21Janes Defence Intelligence
The US Navy (USN) and Pentagon have accelerated efforts to develop and deploy unmanned naval vessels, restructuring organizations and awarding contracts to integrate these systems into the fleet. Admiral Daryl Caudle highlighted the operational value of unmanned platforms, citing their use in conflicts like Ukraine and Iran, and announced the integration of medium unmanned surface vessels (MUSVs) into strike-group operations. To streamline development, the USN established the Robotic and Autonomous Systems Warfighting Development Centre (RASWDC) in September 2026, focusing on rapid testing and operational employment, while the Pentagon oversees acquisition and funding. Private industry interest in the growing market has surged as the USN shifts from experimentation to real-world deployment.
56Smart Maritime Network2026-10-13
SEA.AI’s machine vision technology has been integrated into MARTAC’s unmanned surface vessels (USVs), enabling real-time AI-based detection and classification of surface objects using electro-optical and thermal sensors. The system autonomously identifies vessel types, headings, and proximity without operator input, enhancing USV capabilities for missions like the T38 Devil Ray’s eight-day autonomous operation in Sea State 5 conditions. MARTAC and SEA.AI emphasize the technology’s role in closing gaps for fully autonomous maritime operations. The integration is part of MARTAC’s focus on advanced sensor solutions for its USV range, including the MANTAS and Devil Ray models.
57Hellenic Shipping News2026-10-07
The IMO’s Maritime Autonomous Surface Ships (MASS) Code, adopted in 2026 as a non-mandatory framework, sets goal-based safety and performance standards for autonomous vessels, with a mandatory version planned for 2032. Translating its broad requirements—such as defining an Operational Design Domain (ODD) and fallback protocols—into practical engineering solutions remains a key challenge, particularly for complex operations like harbor tugs. Industry, regulators, and engineers must collaborate to establish traceable, vendor-neutral interpretations of the Code to avoid fragmentation. The IMarEST’s MASS Special Interest Group aims to facilitate this by fostering shared frameworks and operational confidence before the Code becomes mandatory.
58Phys.org2026-08-21
Autonomous ship operators' liability in oil spill incidents is still legally uncertain as of 2026. Current regulations do not clearly define who is responsible—whether the shipowner, software developer, or manufacturer. This lack of clarity complicates compensation claims and legal accountability. The issue remains unresolved despite advancements in maritime autonomy.
59Marine Industry News2026-06-26
A Royal Navy uncrewed surface vessel (USV) collided with a yacht in a busy harbor, prompting concerns about the safety and reliability of autonomous vessels in high-traffic areas. The incident has sparked debate over regulations and operational protocols for unmanned maritime systems. Authorities are reviewing the circumstances to assess potential risks and improvements. The event highlights challenges in integrating autonomous technology into shared waterways.
The paper explores legal and security challenges posed by Maritime Autonomous Surface Ships (MASS) under the UK’s Aviation and Maritime Security Act (AMSA) 1990. It highlights that current frameworks, designed for physical threats, fail to address risks like cyberattacks and remote commandeering unique to autonomous vessels. The author proposes adapting AMSA to include a graded system for unauthorized interference, categorizing incidents by severity. This approach aims to strengthen maritime security and establish the UK as a leader in regulating autonomous shipping.
61hromadske2026-11-04Hromadske
A German defense startup, Stark Defence, plans to launch the unmanned vessel *Vanta 24* in 2027 to monitor Russia’s shadow fleet and protect undersea infrastructure in the Baltic and North Seas. The 24-meter vessel can carry up to 50 metric tons of payload, including weapons, and operate at speeds over 64 km/h without a crew. Stark claims the vessel will be far cheaper and faster to produce than traditional warships, with deployment possible within months. The project aims to counter Russian hybrid threats, though analysts note challenges in scaling up the technology.
The paper explores the impact of Autonomous Maritime Vehicles in Law Enforcement (AMVLEs) on maritime security and legal frameworks in the South China Sea. It argues that while AMVLEs do not create new tensions, they may worsen existing ones by complicating identification, navigational rights, and lawful responses during encounters. The authors conclude that adapting existing UNCLOS rules—through consistent application, clear state responsibility, and regional cooperation—can address these challenges without requiring a new legal regime. Operational restraint and confidence-building measures are recommended to reduce risks and maintain UNCLOS as the regional legal foundation.
63The Portland Press Herald2026-10-23
A SeaTrac uncrewed surface vessel (USV) lost contact with researchers on October 12 while operating 30 miles southeast of Frenchman Bay, Maine. The project team, affiliated with the Northeastern Regional Association, regained communication with the vessel on October 23. No further details on the cause of the outage or the vessel's condition were provided. The incident was reported by the *Portland Press Herald*.
64Riviera Maritime Media2026-10-16
Automation in ships does not equate to full autonomy, as policy and insurance frameworks remain underdeveloped. Current regulations and risk assessments struggle to address the complexities of uncrewed or highly automated vessels. Legal accountability and liability gaps persist, complicating adoption. The article argues that true autonomous shipping requires clearer governance and updated insurance models.
This paper introduces a hierarchical robust control system for autonomous berthing of Maritime Autonomous Surface Ships (MASS) to handle dynamic propulsion-mode switching and environmental disturbances. The method includes a reverse spatial-temporal planning algorithm, a decoupled adaptive guidance law, and a dynamic-truncation SQP allocation strategy to improve thrust management and actuator transitions. Testing under strong wind-current conditions (Beaufort force 7) demonstrated sub-meter berthing accuracy and reduced yaw-rate deviation by 13.8% compared to conventional methods. The system also prevented collisions with the shoreline during sudden disturbances.
66리드경제2026-09-23
Maritime AI received a 26.1 billion won national project to develop an AI safety platform for autonomous ships. The initiative aims to enhance the safety and reliability of self-navigating vessels. The project was announced by 리드경제 on September 23, 2026. No specific technical details or outcomes were disclosed in the report.
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.
This paper provides a supporting dataset for liability governance in AI-powered Maritime Autonomous Surface Ships (MASS). It includes legal and regulatory materials, a comparative liability analysis, and a Hybrid Multi-Layer Liability Governance Framework. The dataset underpins research on structuring accountability for MASS operations. Published in 2026, the work is authored by P. Saleem Akram.
69Travel And Tour World2026-05-04
Orca AI and Samsung Heavy Industries have partnered to develop autonomous vessel technologies for the cruise tourism industry. The collaboration aims to enhance navigation and safety features using AI-assisted systems. This initiative is expected to support the growth of cruise tourism by improving operational efficiency and reliability. The project focuses on integrating advanced AI solutions into maritime operations.
The paper by Steven Dauer (2026) addresses certification gaps for Maritime Autonomous Surface Ships (MASS), as current regulations assume human crews. It proposes an Operational Design Domain (ODD) framework to define safe operating limits—such as environmental conditions, sensor reliability, and traffic scenarios—for autonomous vessels in open ocean settings. The framework includes cascade triggers for degraded conditions and a Mandatory Scenario Coverage Matrix to ensure thorough testing. It aligns with Flag State oversight and Classification Society guidelines, offering a structured approach for integrating autonomy into maritime systems.
71Military Embedded Systems2026-04-21
Leonardo DRS unveiled a counter-unmanned aerial system (C-UAS) designed for autonomous surface vessels at the 2026 Sea-Air-Space exposition. The system aims to detect, track, and neutralize drone threats to naval operations. It integrates advanced sensors and effectors tailored for unmanned maritime platforms. The technology was showcased as a solution for enhancing vessel security in contested environments.
72Lloyd's Register2026-10-12
Sagar Defence and Lloyd’s Register (LR) partnered to accelerate the certification of autonomous maritime systems. The collaboration aims to establish standards and frameworks for safe and reliable autonomous vessel operations. Their joint efforts focus on advancing regulatory approval processes for these technologies. The initiative supports the broader adoption of autonomous solutions in the maritime industry.
73PR Newswire2026-10-08
Galaxia and Maritime Launch Services have partnered to develop an autonomous flight safety system for Spaceport Nova Scotia. The collaboration aims to enhance launch safety by integrating advanced automation into flight monitoring and termination processes. The system will support Maritime Launch Services' operations at the spaceport. No specific technical details or timelines were provided in the announcement.
74openalex2026-10-06Kristin Kerem, Deniece Melissa Aiken, Kristīne Carjova, Ulla Pirita Tapaninen +1 moreDOI ↗ (opens in a new tab) This study explores risk-based regulatory measures for testing autonomous ships in the Gulf of Finland, advocating for a proactive approach instead of reactive accident-driven policies. Using documentary analysis, interviews, and legal research, it assesses how risk-based frameworks balance innovation with safety in maritime technology. The research highlights the importance of stakeholder collaboration, particularly joint risk assessments, to develop standards without stifling progress. Findings suggest that shared knowledge between corporate and governance bodies supports effective regulatory integration.
This study introduces a reliability-based robust design optimization (RBRDO) method for improving unmanned surface vessel berthing trajectory planning under uncertainty. The approach integrates line-of-sight guidance, artificial-potential-field obstacle avoidance, and sliding-mode control, while modeling collision risks for various obstacle shapes and accounting for vessel-position uncertainty. Simulations demonstrate that RBRDO outperforms baseline and deterministic optimization methods by reducing terminal distance errors, failure probability, and variability in berthing performance. The method enhances robustness and reliability in uncertain berthing conditions.
76Splash2472026-09-23
German researchers are creating an AI system to assist vessel traffic controllers in managing waterways with conventional, automated, and autonomous ships. The LEAS-PRO project, led by Fraunhofer FKIE, will develop a demonstrator that analyzes traffic data and provides risk assessments and recommendations to operators. The goal is to enhance situational awareness and reduce cognitive strain without replacing human controllers. The project is set to continue until July 2028.
77crossref2026-09-08Sergey I. Kondratyev, Evgeniy V. Khekert, Nikita V. Martyushev, Boris V. Malozyomov +5 moreDOI ↗ (opens in a new tab) A risk-aware multisensor fusion system was developed for autonomous navigation and mooring in confined waters, integrating data from RTK-GNSS, inertial sensors, radar, LiDAR, cameras, and other sources. The system uses fault detection, sensor-quality assessment, and dynamic authority allocation between automation and operators to maintain reliability. Testing over five days with 40 runs and 480 evaluation epochs showed horizontal-position and heading errors of 0.043 m and 0.176°, respectively, under normal conditions. The system detected all 64 fault events, with 99.3% protection-level coverage for single faults and 100% for combined faults, ensuring safe operation even under degraded sensor conditions.
This study introduces a Deep Q-Network (DQN)-based path planning method for autonomous fishing vessels to enhance safety by reducing wave-induced roll motions. The approach integrates roll motion reduction into the reward function and combines maneuvering models with hydrodynamic analyses. Simulations showed the vessel adjusted its heading to minimize roll, reducing average and maximum roll responses by 3% and 2%, respectively, at a 1.0 m wave height, while maintaining path tracking with a slightly longer route. Future work will include testing in more complex environments and validating the model through physical experiments.
This paper introduces a machine learning operations (MLOps) framework for real-time anomaly detection in autonomous surface ships, focusing on engine conditions. The system uses a hybrid model combining an attention LSTM autoencoder and isolation forest to detect subtle anomalies across engine components. To handle data drift, an onboard MLOps pipeline monitors sensor data shifts and autonomously retrains models when performance drops. Tests on a fault simulation testbed show the system maintains detection reliability under changing conditions.
80Baird Maritime2026-05-26
The International Maritime Organization (IMO) has finalized a new safety code for autonomous ships. This code establishes guidelines to ensure the safe operation of vessels with varying levels of automation. It addresses risks and regulatory requirements for maritime autonomy. The framework is expected to support the growing adoption of autonomous shipping technologies.
This paper presents a stereo-vision system for ship detection and localization on Unmanned Surface Vehicles (USVs). The system uses GS-YOLO, an improved version of YOLO11n with added modules (GLSA, BiFPN, and SIoU loss), to enhance small ship detection accuracy while reducing model parameters by 17.8%. For localization, a cascaded filtering algorithm combining median and Kalman filtering processes depth data to minimize errors caused by dynamic interference. Tests show GS-YOLO achieves 93.5% mean average precision, and the localization method reduces positioning error by up to 89.3% within 50 meters.
The paper analyzes legal challenges posed by maritime autonomous surface ships (MASS) to international maritime law, including UNCLOS, SOLAS, COLREGs, and STCW, which were not designed for autonomous vessels. It identifies gaps in the current legal framework and evaluates Vietnam’s existing regulations. The authors recommend a multi-tiered approach: creating regulatory sandboxes, updating domestic maritime laws, and engaging in international norm development for MASS. The study aims to improve Vietnam’s legal readiness for autonomous shipping.
83112.ua2026-11-04
The Vanta 24 is an unmanned vessel developed by Stark to protect undersea cables in European waters. The vessel is designed to monitor and safeguard critical infrastructure from potential threats. Its deployment aims to enhance security for communication and energy networks. No specific operational details or outcomes are provided in the text.
84LOOSE CANNON | Peter Swanson2026-10-29
The Lake Erie accident report, published on October 29, 2026, attributes the incident to failures in watchstanding procedures for an uncrewed vessel. The investigation highlights lapses in monitoring and oversight as key factors in the accident. The report was authored by Peter Swanson for *Loose Cannon*. No specific details on the accident's consequences or corrective measures are provided.
85WorkBoat2026-10-27
The National Transportation Safety Board (NTSB) is urging the establishment of safety standards for uncrewed vessels following a collision in Lake Erie. The incident prompted concerns about the lack of regulations governing autonomous or remotely operated ships. The NTSB emphasized the need for guidelines to prevent future accidents involving such vessels. No specific details about the collision or proposed standards were provided in the report.
86Portland Press Herald - Maine Sunday Telegram2026-10-23
Researchers reestablished contact with an uncrewed vessel that had gone missing off the coast of Maine. The vessel, used for scientific research, lost communication earlier in the week. No details on the cause of the disruption or the vessel's condition were provided. The team is assessing its status following the reconnection.
This study presents a multi-fidelity reinforcement learning (RL) framework to improve the development of autonomous surface vehicles (ASVs). The approach trains policies first in a low-fidelity simulation for speed, then refines them in high-fidelity physics, reducing training time by 77.1% and enabling testing of 80 policy configurations within the same computational budget. The method successfully transferred navigation skills—waypoint reaching, station-keeping, and obstacle avoidance—to a real ASV in a harbor under Sea State 4 conditions. Results confirm the framework effectively bridges the simulation-to-reality gap while enhancing safety and cost-efficiency.
88Breaking Defense2026-10-19
The Defense Innovation Unit (DIU) has initiated the second phase of its SWAP-USV prize challenge, offering up to $40 million for mature unmanned surface vessels (USVs) deployable within 120 days. This phase targets USVs equipped with hard-kill counter-air systems and resilient sensors to detect and neutralize airborne threats like Groups 1–3 UAS and rotary-wing aircraft, with a minimum range of 200 nautical miles and a speed of 10 knots. Submissions are due by November 30, with in-water testing set for early 2027, while the final phase (Sprint 3) will conclude by summer 2027. The competition, backed by $200 million for potential contracts, aims to address cost-effective, persistent defense against low-signature threats.
This study presents a hierarchical path-planning framework for unmanned surface vehicles, combining global routing and local collision avoidance while adhering to maritime rules. The method integrates adaptive A* and RRT* algorithms for global planning, alongside artificial potential fields and dynamic window approaches for local adjustments. Simulations showed 81.7% success in static planning, with lower success rates (63.3%) in integrated navigation under perturbed conditions. The approach proved feasible but highlighted inefficiencies like detours and stalled trajectories, requiring further improvements.
This paper updates maritime security research, addressing challenges from digitization, automation, cyber-physical risks, and geopolitical threats. It expands on risk identification, decision-making, and system resilience, covering collision-risk sensing, human-technology interaction, and port safety. The studies highlight gaps like limited validation, incomplete causal analysis, and weak cross-scale integration. Effective implementation demands trustworthy data, uncertainty management, and coordinated response plans for cyber-physical and security failures.
This study analyzes ship safety domains in the North Sea using AIS data from 2014, focusing on vessels over 45 meters long traveling at 5–25 knots. Results confirm that safety domains are elliptical, with the major axis expanding at higher speeds while the minor axis remains constant, and ship size does not significantly affect domain dimensions. Avoidance maneuvers rely on CPA and TCPA calculations, typically initiated 600–1800 seconds before the closest point of approach, with modest course changes to maintain the elliptical domain. The findings suggest elliptical domains could improve conflict-detection algorithms and navigation systems for both crewed and autonomous ships.
92Safety4Sea2026-06-03safety4sea
The article reports on newly launched initiatives aimed at improving AI infrastructure and the design of autonomous vessels. These efforts focus on enhancing technological capabilities in maritime operations. The projects seek to support innovation in shipping and related industries. No specific methods or outcomes are detailed in the text.
This paper introduces a structured method for designing autonomous ships by combining traditional ship design principles with autonomy-specific requirements. The approach helps generate early concept designs optimized for operational needs, assessing how autonomy affects ship dimensions, layouts, and systems. A case study on a feeder containership demonstrates the method’s application. Future research aims to expand the focus beyond the ship itself to entire autonomous maritime ecosystems.
The paper examines legal, regulatory, and insurance challenges tied to autonomous shipping, emphasizing the need for supportive frameworks. Key terms like "autonomous," "ship," and "cyber risk" are criticized for imprecision, complicating policy and coverage. Existing marine insurance, such as ITCH83 and P&I Club rules, may cover some cyber risks if losses are classified as marine, but gaps could require additional cyber-specific policies. Insurers are expected to demand strict cybersecurity practices as a condition for coverage.
The **Evidence-Unit Mapping (EUM) Database** breaks down 67 studies on Maritime Autonomous Surface Ships (MASS) into 158 specific safety and economic performance claims. It categorizes data by IMO autonomy levels (DoA 1–4), focus areas, and research methods (quantitative, qualitative, or review). Each claim is assigned a binary or weighted impact score (-1, 0, +1) for safety and cost-efficiency. The dataset includes source references, thematic metadata, and direct quotes from the original studies to justify scoring.
96PortNews IAA2026-10-28
South Korea will invest $346 million by 2032 to develop fully autonomous (Level 4) ships, aiming to lead global orders for the technology by 2035. The project, led by two ministries, includes unmanned navigation, automated systems, and testing in domestic and international waters. It builds on a prior $120 million program (2020–2025) that achieved Level 3 autonomy. The initiative is part of a broader maritime AI strategy to boost productivity, safety, and environmental management.
97파이낸셜뉴스2026-10-28
The global autonomous ship market is targeting Level 4 autonomy within six years. This advancement aims to secure fully automated navigation technology for vessels. The focus is on developing systems that require minimal to no human intervention. Industry efforts are accelerating to achieve this milestone by 2032.
98gCaptain2026-10-21
The U.S. Navy is advancing unmanned surface vessels (USVs) from testing to operational use, with recent deployments in the Persian Gulf and alongside the USS Theodore Roosevelt Carrier Strike Group. Successful missions include rescuing downed Army aviators and supporting mine clearance, demonstrating USVs' role in real-world operations. Senior leaders, including the Secretary of War and Navy officials, are prioritizing integration into fleet operations, emphasizing organizational and training reforms. The Navy must now develop clear concepts of operations (CONOPS) to define missions, ownership, and sustainment while continuing experimentation without treating it as a standalone strategy.
99Smart Maritime Network2026-05-22
The International Maritime Organization (IMO) adopted an international safety code for autonomous ships in May 2026. This new regulation establishes global standards to ensure the safe operation of ships with varying levels of automation. The code addresses risks and requirements for maritime autonomous surface ships (MASS). It aims to provide a consistent framework for countries implementing autonomous shipping technologies.
This paper presents a unified, safety-constrained optimization framework for autonomous mining systems, integrating sensor fusion, edge intelligence, and digital twin-based decision support for surface and underground environments. The approach uses mathematical modeling and multi-objective optimization to improve vehicle dynamics, drilling mechanics, and fleet coordination under GNSS-denied and extreme Nordic conditions. Validation through Monte Carlo simulations and statistical testing showed productivity gains of ~24.3%, energy reductions of ~12.8%, and safety risk decreases of ~48.6% compared to baseline systems. Key performance drivers identified include localization accuracy, communication delay, and optimization weighting.
This paper proposes a method to define seakeeping performance criteria for unmanned surface vessels (USVs) to improve their operation in harsh maritime conditions. It reviews seakeeping data from various vessels, including manned ships, to develop a tailored procedure for USVs. A 7-meter-class USV serves as a case study, where preliminary criteria were established and validated through model tests. The goal is to enhance USV design for better performance in joint or independent naval missions.
102safety4sea2026-10-30
A 2026 article by safety4sea examines advancements in autonomous navigation to improve collision avoidance and maritime safety. It focuses on technologies enabling ships to operate independently while reducing human error risks. The piece highlights ongoing developments aimed at enhancing reliability and regulatory compliance in autonomous shipping. No specific methods or results are detailed in the provided text.
The paper explores legal challenges posed by autonomous fishing vessels (AFVs) under the UN Convention on the Law of the Sea (LOSC). It highlights gaps in the LOSC framework, including issues of vessel classification, jurisdiction, safety, and environmental protection due to its human-centric assumptions. The study argues that AFVs require legal adaptations to address ambiguities in coastal and flag State responsibilities. Such changes are needed to ensure regulatory clarity and sustainable fisheries management.
104comparethecloud.net2026-10-05
Britain should prioritize autonomous technology investments in harbor operations over ocean crossings, focusing on defined transport tasks like container transfers between terminals. Singapore’s autonomous feeder vessel program serves as a model, emphasizing reliability, safety, and integration with existing workflows rather than immediate cost savings. British suppliers could contribute by addressing specific challenges such as degraded visibility, cybersecurity, or terminal integration, but must clarify responsibilities and boundaries in contracts. Regulatory approval in the UK depends on vessel size, operating area, and use, requiring early engagement with the Maritime and Coastguard Agency to establish a clear pathway.
This study assesses MEMS inertial sensors for autonomous naval platforms, comparing low-cost and tactical-grade sensors under calm and rough sea conditions. Low-cost sensors show rapid error growth without external aiding, while tactical-grade sensors offer better stability. An Extended Kalman Filter (EKF) reduces drift by 60–80% when combined with periodic GNSS updates. Performance declines in high sea states due to increased noise and nonlinear motion.
This study presents a machine-learning maritime security system using YOLOv8 for pirate detection in low-light and adverse weather, trained on an augmented dataset. The system assesses threat levels by analyzing vessel size, speed, and heading to differentiate pirate skiffs from benign boats, reducing false positives. It calculates optimal evasive maneuvers, finding zigzag patterns most effective for unarmed ships. The framework operates in real-time on standard hardware, offering a proof-of-concept for early threat mitigation.
This paper proposes a new architecture for situational awareness in Level 4 autonomous marine vessels, addressing limitations in traditional data fusion methods that fail to differentiate sensor failures, accuracy issues, or cyberattacks. The system includes a non-switchable core of essential sensors, a Sensor Trust Manager to isolate unreliable data sources, and a navigation scenario classifier that adjusts sensor confidence weights dynamically. The approach shifts from data fusion to "source trust management," introducing meta-awareness to monitor both the environment and sensor reliability. The design aims to comply with maritime safety regulations while improving unmanned navigation safety.
The paper introduces CD-HSSRL, a reinforcement learning framework for autonomous amphibious robots navigating both water and land. It addresses challenges like discontinuous dynamics and safety risks by combining a global reachability planner, hierarchical switching policies, and a safety-constrained controller. Tests on multiple benchmarks show a 15% improvement in transition success and a 40% reduction in collisions compared to existing methods. The framework offers a unified solution for safe cross-domain navigation in amphibious robots.
109IndexBox2026-11-04
Bureau Veritas awarded an Approval in Principle (AiP) to OceanAlpha for its L42B uncrewed survey vessel in November 2026. The certification recognizes the vessel’s compliance with safety and operational standards. The L42B is designed for autonomous hydrographic and oceanographic survey missions. This development highlights advancements in uncrewed maritime technology.
110openalex2026-10-29Shaffiyah Cantika Kamia, Suharyono Soemarwoto Hadiningrat, Jones Zenas Rante, Rudianto Rudianto +1 moreDOI ↗ (opens in a new tab) This study explores the adoption of Unmanned Lighthouse Systems in Banjarmasin, Indonesia, highlighting benefits like a projected 40% cost reduction, improved safety, and compliance with IMO and IALA standards. Challenges include environmental constraints, regulatory gaps, digital skill shortages, unreliable power and telecoms, and cybersecurity risks. Researchers used interviews, observations, and document analysis to develop a three-phase implementation roadmap. The findings offer a socio-technical framework for modernizing maritime navigation in developing nations.
111Marine Insight2026-10-29
A Bulgarian naval vessel rescued all 18 crew members—14 Filipinos and four Ukrainians—after three naval drones attacked the Liberian-flagged container ship *Contship Jet* 21 nautical miles off Bulgaria’s Black Sea coast on October 28, 2026. The ship, en route from Israel to Romania with 421 containers, was struck by uncrewed surface vessels, with surveillance confirming three hits. Bulgaria’s Defence Ministry, alongside a French patrol aircraft, monitored the incident and dispatched rescue teams, transporting the crew to Varna for medical checks. NATO and EU allies condemned the attack, with Bulgaria seeking enhanced maritime surveillance and counter-drone support amid rising tensions in the region.
112TradeWinds News2026-10-28
US investigators warn that autonomous vessels require improved lookout systems to prevent collisions and ensure safety. The alert highlights concerns over current technology's ability to detect and respond to hazards as effectively as human crews. Regulatory and industry efforts are needed to address these risks in unmanned shipping. The issue was raised following recent incidents involving autonomous ships.
113Interesting Engineering2026-10-19
A 368-ton former US Navy vessel, modified with HD Hyundai’s VAone autonomy suite and Anduril’s Lattice platform, completed a 3.5-hour autonomous sea trial off Long Beach, California. The exercise tested navigation, formation sailing, mission adaptability, and responses to simulated machinery failures, monitored remotely by US and South Korean defense officials. The vessel demonstrated integrated autonomy in navigation, machinery management, and damage control without onboard crew intervention. The trial aimed to showcase technology for future unmanned naval operations, though no procurement award has been announced.
This paper presents a formation control framework for unmanned surface vessels (USVs) to improve cooperative tracking safety in complex marine environments. It uses a prescribed performance control method with adjustable boundaries to minimize tracking errors and reduce collision risks, while an integral disturbance observer addresses model uncertainty and external disturbances. A control barrier function (CBF) ensures safety by solving a quadratic programming problem, balancing formation tracking and security. Simulations show the method outperforms others in response speed, disturbance rejection, and input smoothness.
115rivieramm.com2026-09-14
DNV will provide classification services to support Fassmer’s development of naval autonomous vessels. The collaboration aims to advance the design and safety standards for uncrewed ships in naval applications. Fassmer, a German shipbuilder, is focusing on integrating autonomous technologies into its naval projects. The partnership will ensure compliance with regulatory and operational requirements.
116Sea News2026-08-20
The article highlights cybersecurity risks in autonomous shipping due to increased connectivity. It warns that reliance on digital systems exposes vessels to potential hacking, data breaches, or operational disruptions. These vulnerabilities could compromise safety, navigation, and cargo security. The piece emphasizes the need for stronger cyber defenses in maritime automation.
This study presents a fire detection system for autonomous ships using a four-channel model combining RGB, infrared (IR), and ultraviolet (UV) sensors with LiDAR for localization. The system uses an Xception-based network for RGB+UV images and a dense-based network for UV time-series data, reducing false alarms from fire-like sources like welding. A YOLOv7 model with LiDAR projection improved fire source localization accuracy over traditional triangulation methods. Tests in open and occluded environments confirmed the system's effectiveness.
118U.S. Naval Institute2026-08-01
The U.S. Naval Institute argues that autonomous vessel programs overlook roll stabilization as a critical specification. Current designs prioritize sensors and software but neglect the vessel's physical stability in rough seas. Without proper roll stabilization, autonomous systems may fail to perform reliably. The article emphasizes that platform stability should be a foundational requirement in development.
119TipRanks2026-06-06
Saronic Technologies demonstrated an autonomous vessel designed for U.S. port security applications. The showcase highlighted its potential use in monitoring and protecting port infrastructure. The technology aims to enhance maritime security through unmanned operations. No specific technical details or deployment timelines were provided.
This study examines how eye-tracking data can improve the design of maritime navigation instruments like ECDIS and radar. Researchers are analyzing gaze patterns, fixation durations, and cognitive workload in simulated bridge environments to identify ergonomic flaws such as poor symbol placement, color contrast, and visual clutter. The goal is to propose redesigns that reduce human error, particularly for less experienced navigators. Findings may inform both equipment manufacturers and maritime training programs.
This paper examines the critical role of Main Switch Boards (MSBs) in autonomous ships, focusing on power management, generation, and distribution to ensure uninterrupted operation. It introduces SEFR (Safety, Effectiveness, and Reliability) contacts, which must meet specific electrical and mechanical standards to prevent supply failures. The study categorizes contacts into three criticality levels: Level 1 (non-essential), Level 2 (essential), and Level 3 (vessel survival-dependent), with varying redundancy and control measures. The SEFR framework is applied to design MSB supply lines, ensuring continuous power for autonomous vessels.
GeoShield is a multi-layered defense framework designed to detect and correct adversarial tampering in autonomous vehicle navigation maps. It uses OpenStreetMap metadata and NASA SRTM elevation data to identify attacks like label flipping, road-direction manipulation, and speed-limit spoofing. The system employs heuristic validation, graph-based anomaly detection (e.g., Isolation Forest, HMMs, GraphSAGE), and selective re-verification via the Overpass API. Tested on European and U.S. road networks, it aims to flag and confirm tampered map segments with high accuracy.
The paper by Melis Özdel (2026) examines the role of the CMI International Working Group on Maritime Autonomous Surface Ships (MASS) in developing legal frameworks for autonomous vessels. It highlights the group’s growing influence in addressing challenges like liability, governance, and regulatory adaptation for remote-controlled and autonomous ships. The chapter critically discusses debates, including whether a strict liability regime should apply to MASS. It combines scholarly and practical insights to contribute to discussions on international maritime law evolution.
This study compares multi-criteria decision-making tools to prioritize failure modes in naval systems for sustainable maintenance. It applies the Analytic Hierarchy Process (AHP) alone and combined with ELECTRE I to rank failure modes using criteria like Severity, Occurrence, Detection, Economic Factor, Sustainability Maintenance Strategies, and Management and Data Security. The top-ranked failure modes from both methods are compared to identify similarities and differences. A sensitivity analysis assesses the robustness of the results.
125Engineering and Technology Magazine2026-04-08
The UK has deployed an autonomous vessel designed to detect and destroy underwater mines. This unmanned system aims to enhance naval safety and operational efficiency. The technology reduces risks to human divers and crewed ships. The initiative reflects advancements in maritime defense automation.
126Porttechnology.org2026-10-14
The IMO has introduced legislation to regulate the safety and security of increasingly automated shipping technology. The article discusses the transition from theoretical Maritime Autonomous Surface Ships (MASS) codes to practical maritime applications. Challenges remain in implementing these regulations effectively. The focus is on bridging the gap between policy and real-world maritime operations.
127Odessa Journal2026-10-05
A cargo ship near Odesa was struck by a Russian drone, leaving it without a crew. The damaged vessel is now drifting uncontrollably toward Bulgaria. The incident occurred in the Black Sea amid ongoing regional tensions. No further details on casualties or the ship’s condition were provided.
128Shipping Telegraph2026-07-16
P&I Clubs have established a new insurance framework for autonomous vessels. The initiative aims to address risks and liabilities associated with uncrewed ships. This development marks a significant step in supporting the maritime industry's shift toward automation. The pathway provides coverage tailored to the unique challenges of autonomous operations.
129Army Recognition2026-06-17
The U.S. Army conducted tests of unmanned surface vessels (USVs) in Philippine waters to enhance the protection of logistics ships. The trials aimed to evaluate the effectiveness of these autonomous systems in safeguarding maritime supply routes. The exercise took place amid growing regional security concerns. No specific outcomes or technical details were disclosed in the report.
This paper introduces a falsification-driven reinforcement learning (RL) method to improve rule compliance in autonomous maritime vessels. The approach generates adversarial training scenarios where vessels violate maritime traffic rules, expressed as signal temporal logic specifications. Experiments on open-sea navigation with two vessels show the method produces more relevant training scenarios and enhances consistent adherence to traffic rules. The study highlights the use of temporal logic robustness measures to extend maritime traffic rules.
This paper reviews how surface mine planning must adapt to integrate Autonomous Haulage Systems (AHS) in open-pit metal mining. Key changes include workforce dynamics, communication infrastructure, and haul road design, with debates on optimal road width and load channelization. The study emphasizes the need for holistic, data-driven mine design and better human-autonomous collaboration. Empirical validation of workforce transition strategies is also highlighted for safer and more effective AHS deployment.
WorldSense is a framework designed to improve autonomous vehicle safety in rare or high-risk driving scenarios. It combines predictive world modeling, anomaly detection, and safety-aware planning by encoding the environment with a CNN-based system and predicting future scenes using a recurrent memory module. The system detects anomalies in real time and adjusts trajectories to avoid collisions. Tests on CARLA and nuScenes show a 34.2% reduction in collisions and a 14.6 percentage point increase in route completion compared to transformer-based baselines.
Researchers at RWTH Aachen University are developing a structured safety concept for integrating autonomous machinery in surface mining, addressing the lack of standardization in mixed-traffic operations. A key component is an integrated safety control system relying on perception sensors, though their performance under harsh mining conditions remains poorly understood. To study this, a long-term test stand was built at a quartz sand open-pit mine to evaluate sensor reliability across varying environmental influences. The work aims to improve safety and efficiency in autonomous mining operations.
This paper examines how current and future regulations impact AI systems and product liability, specifically in the maritime sector. It compares existing transportation norms, particularly from the road sector, with maritime laws, focusing on AI integration. The analysis covers contractual and non-contractual liability rules under European legislation for defective AI products. The authors highlight the need for tailored AI regulations in maritime to address safety and liability, especially for autonomous ships.
This paper presents a mission-planning framework for autonomous marine vehicles conducting seabed surveys, focusing on safety, COLREG compliance, and operator transparency. It introduces a layered architecture for an onshore-supervised surface vessel that generates coverage plans from operator-defined polygons and produces structured reports for underwater vehicle inspections. The system includes a behavior-tree executive, a reinforcement-learning advisor for optimized survey edits, and a risk assessment layer for collision avoidance. The framework is validated through ongoing development of a surface vessel and remote operation center, using repeatable logs and status reporting.
This paper introduces a stochastic reliability framework to assess and compare the safety of manned and unmanned Maritime Autonomous Surface Ships (MASSs). Using Reliability Block Diagrams (RBDs) and Monte Carlo simulations, the method evaluates mission success by treating component failure data as uncertain variables. Applied to a Search and Rescue Patrol Vessel, results show unmanned configurations can match or exceed manned reliability under moderate uncertainty but converge as uncertainty increases. The approach aids reliability-focused design for autonomous marine systems.
This paper presents a benchmarking framework to standardize the evaluation of search-based scenario selection methods (SBSSMs) for validating autonomous systems. The framework offers a domain-independent environment with synthetic test instances, standardized metrics, and reference implementations to improve reproducibility and comparability. It abstracts application-specific details while preserving structural patterns from real-world scenarios, such as maritime simulations. The tool aims to facilitate method comparison and advance SBSSM development across fields like automotive safety.
The paper examines security vulnerabilities in the Global Maritime Distress and Safety System (GMDSS), highlighting risks like unauthorized access, false distress alerts, and manipulated safety information due to weak authentication and validation. It argues that these issues stem from systemic gaps in governance, procedures, and security integration rather than technical failures alone. The study calls for a holistic approach, combining technological, procedural, human, and regulatory measures to strengthen GMDSS security. Findings emphasize the need for coordinated strategies to address interconnected vulnerabilities in voice and data communication without undermining maritime safety.
139SSBCrack2026-05-06
Textron Systems upgraded its Common Unmanned Surface Vessel (CUSV) by integrating an advanced air defense system. The enhancement aims to improve the vessel's capability to detect and counter aerial threats. No specific technical details or operational timelines were provided in the announcement. The upgrade reflects ongoing efforts to bolster unmanned maritime defense technology.
140The Waterways Journal2026-11-06
The NTSB issued six recommendations on October 27, 2026, urging stronger safety standards for uncrewed surface vessels (USVs) after investigating a 2024 collision on Lake Erie between a NOAA-operated USV and a recreational vessel. The incident caused significant damage ($186,000 to the USV, $100,000 to the recreational vessel) and one minor injury, with the NTSB citing poor visibility and lack of electronic detection as key factors. The NTSB called on the U.S. Coast Guard to establish national standards for USV perceptibility, collision avoidance, and navigational safety, while also recommending design changes and stricter operational monitoring by manufacturers and agencies like NOAA. Currently, no industrywide standards exist for USVs in U.S. waters.
141Boating Industry2026-10-30
The National Transportation Safety Board (NTSB) has urged the implementation of stronger safety standards for uncrewed surface vessels (USVs). This call follows investigations into incidents involving autonomous or remotely operated boats. The NTSB recommends improved regulations to address risks such as collisions, navigation failures, and operational oversight. The proposal aims to enhance safety for both USVs and traditional maritime traffic.
142η ναυτεμπορικη2026-10-29PROTINEWS
A Greek-owned containership sank off the coast of Bulgaria after being attacked by three maritime drones. The incident occurred in late October 2026, as reported by PROTINEWS. No additional details about casualties or the perpetrators were provided in the report. The attack marks a rare use of unmanned maritime drones in a shipping assault.
143δεδομενο2026-10-28
A Greek-owned cargo ship was attacked by sea drones in the Black Sea, off the coast of Bulgaria, on October 28, 2026. The incident occurred in international waters, though near Bulgarian territorial boundaries. No further details on casualties or damage were provided in the report. The attack highlights ongoing security concerns in the region.
144NTSB (.gov)2026-10-27
The NTSB recommended stronger safety standards for uncrewed surface vessels after investigating a collision in Lake Erie. The incident highlighted gaps in current regulations governing autonomous or remotely operated boats. The board urged the U.S. Coast Guard to develop and enforce updated guidelines to prevent similar accidents. No specific details about the collision or proposed standards were provided in the announcement.
145Hydro International2026-10-20
Sentiq Defence, founded by retired Italian Navy commander Antonio J. Belfiore, has launched as an integrator of autonomous and remotely operated maritime systems for defense, security, and blue economy sectors. The company offers uncrewed surface vessels (USVs), underwater surveillance sonars, ROVs, and aerial drones, aiming to simplify integration and provide turnkey solutions with training and support. Based in Italy, Sentiq focuses on addressing fragmented markets by tailoring commercial-off-the-shelf (COTS) systems to customer needs under the principle "command your space." Its growth plan includes expanding partnerships, building a local integration hub, and enhancing training and support services.
146worldenergynews.gr2026-10-20
Maritime drones and stealth submarines are transforming naval warfare by enhancing surveillance, reducing detectability, and increasing operational flexibility. These technologies shift power dynamics in contested regions like the Aegean, where traditional naval dominance may be challenged. The article highlights potential risks and strategic implications for Greece and neighboring countries. Advances in unmanned systems and submarine concealment could redefine military balance in the area.
The paper introduces an Explainable Decision Graph (EDG) framework to improve transparency in Autonomous Multi-Agent Systems (MAS) used in critical fields like healthcare and finance. EDGs structure agents' reasoning, communications, conflicts, and decisions as interconnected graph components, enabling verification against safety and policy constraints. The framework aims to provide clear, multi-level explanations for users, developers, and auditors. Evaluation will focus on metrics like fidelity, traceability, and computational efficiency, with results pending further implementation.
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.
The paper discusses the growing importance of maritime safety and risk assessment due to trends like larger vessels, busier shipping routes, and the adoption of cleaner fuels and autonomous navigation. It highlights the shift toward data-driven decision support systems in the industry. The focus is on addressing emerging challenges in safety and risk management. The work reflects advancements in response to evolving maritime operations.
The paper discusses the importance of Launch and Recovery Systems (LARS) for Unmanned Underwater Vehicles (UUVs), highlighting their role in mission operability and safety. It explores fixed, modular, and mobile LARS solutions, including autonomous docking systems for AUVs. The text also covers manipulator systems used in underwater intervention tasks, primarily by ROVs and AUVs. Emerging technologies like soft actuators and bio-inspired underwater robot designs are noted as areas of growing interest.
This study introduces a learning-based expert strategy for autonomous robotic endovascular interventions, separating high-level decision-making from low-level execution to improve safety and consistency. The method uses a reinforcement learning policy for navigation intent, refined by an expert-informed module to enforce clinical norms and vessel constraints. Tests in simulations and real-world robotic setups showed a success rate above 96%, a 29.3% reduction in operational steps, and a 13% decrease in trajectory variance. The approach enhances efficiency, predictability, and standardization compared to baseline methods.
Jonathan Earthy’s paper outlines the development of ergonomics standards, showing their shift from product-focused rules to principle-based approaches for robotic, intelligent, and autonomous (RIA) systems. It emphasizes human-centered design, where users are seen as active agents, and highlights key standards like ISO 9241-210 and ISO 11064 for ensuring usability and safety in automation. The chapter uses maritime examples to illustrate how these standards apply to autonomous ships. It argues that standards now serve as design tools to embed trust and resilience in intelligent systems.
153Penningtons Manches Cooper2026-05-26
The article warns about legal risks tied to autonomous vessels before the mandatory MASS Code takes effect. It advises maritime stakeholders to address liability, insurance, and regulatory compliance issues proactively. Failure to act early may lead to costly disputes or operational disruptions. The MASS Code will standardize rules, but preparation is critical to avoid legal pitfalls.
This study explores how augmented reality (AR) can be integrated into maritime navigation to assist young navigators. Based on a review of existing research, AR improves situational awareness by displaying navigational data directly in the user’s field of view, reducing distractions and aiding performance in low-visibility or high-traffic scenarios. It also supports team decision-making through real-time, context-aware information sharing. However, its effectiveness depends on well-designed interfaces and proper training.
155UK Defence Journal2026-04-15
Autonomous vessels demonstrated superior performance compared to crewed surveys in recent evaluations, as reported at the Underwater Defence & Security (UDT) conference. The findings suggest that unmanned systems can conduct surveys more efficiently and effectively. This development highlights potential advancements in maritime data collection and defense operations. The UK Defence Journal presented these insights on April 15, 2026.
156gCaptain2026-10-29
A Greek-operated, Liberian-flagged container ship, *CONTSHIP JET*, sank on October 28, 2026, after being struck by three naval drones in Bulgaria’s Exclusive Economic Zone. All 18 crew members were rescued, but the attack—likely carried out by a Russian-designed drone—escalates concerns over Black Sea shipping safety amid Russia’s war in Ukraine. Bulgaria reported at least six similar drone attacks this month, with some suspected to benefit Russia, though Moscow denies involvement. The vessel’s cargo, including hazardous materials, showed no immediate pollution signs after sinking.
157Marine Insight2026-10-26
The U.S. Navy’s Orca XLUUV, its largest uncrewed submarine, completed a 1,000+ nautical mile voyage in the eastern Pacific in July 2026, marking the longest distance traveled by an XLUUV-class system. Designed for a 6,500 nautical mile range, the diesel-electric vessel supports missions like surveillance, mine warfare, and reconnaissance, operating mostly submerged with rare battery recharges. Despite an $885 million investment and eight years of development, the program faces delays, technical challenges, and uncertainty about becoming an official program of record. Five prototypes are expected by late 2026, though autonomy, battery endurance, and software modifications remain key hurdles.
This paper introduces an Intelligent Runtime Safety Monitoring framework for autonomous multi-agent systems (MAS) used in applications like autonomous vehicles and robotics. The framework continuously monitors agent states, actions, and communications during operation, integrating safety verification, risk assessment, trust estimation, and adaptive corrections. It can respond to safety risks by allowing, warning, blocking, or escalating events for human intervention. The study uses the nuScenes and Waymo Open Motion datasets for evaluation, outlining data processing and analysis methods but does not yet present completed benchmark results.
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.
This paper reviews AI applications for reducing human-factor risks in merchant ship operations, analyzing 23 core sources and recent technical evidence. It evaluates AI technologies like computer vision, fatigue analysis, and edge processing, noting high but context-dependent detection performance. A proposed system architecture integrates sensors, edge processing, and fail-safe protocols, while regulatory adaptations for SOLAS, ISM Code, and other frameworks are suggested. The 2026 IMO MASS Code is cited as a precedent for goal-based approval and progressive implementation.
This paper presents a method for safe formation control and path planning of unmanned surface vessels (USVs) in obstacle-heavy and restricted waters. It combines nonlinear model predictive control (NMPC), an adaptive virtual-obstacle replanning strategy, and a formation-transformation approach to navigate narrow gaps and reconfigure vessel arrangements. Simulations in MATLAB and real-USV experiments validate the framework’s ability to handle dynamic obstacles, narrow waterways, and multi-vessel formations. The approach adjusts obstacle parameters iteratively to ensure collision-free trajectories while maintaining formation stability.
This paper introduces a safety assessment framework for autonomous vehicles by combining Fault Tree Analysis (FTA) and Bayesian Network (BN) to address both failures and functional insufficiencies, such as perception and sensor limitations. The approach enables qualitative and quantitative analysis, accounting for dynamic dependencies and uncertainties in real-world driving conditions. A case study on object detection failures identified weather and occlusion as major contributors, responsible for 45.76% and 58.72% of failures, respectively. The framework offers actionable insights for improving autonomous vehicle reliability under the Safety of the Intended Functionality (SOTIF) standard.
163Naval News2026-11-08
Naval Group will build an Unmanned Combat Underwater Vehicle (UCUV) demonstrator for the French Navy, with sea trials set for 2028. The project, funded under a 2026 contract, advances from earlier studies and testing, focusing on autonomous navigation, energy management, and mission adaptability. The UCUV, over 10 meters long, is designed for intelligence, defensive, and offensive missions, with an open architecture for modular payloads and air transport via A400M. Funding for full construction remains pending, dependent on 2027 budget approval.
164Army Recognition2026-11-05
German defense firm Stark Defence is developing the Vanta 24, a 24-meter unmanned drone ship to track Russia’s shadow fleet tankers and protect underwater infrastructure in the Baltic and North Seas. Set for launch in 2027, the vessel will carry anti-ship missiles, a 30 mm naval gun, and long-range radar, enabling surveillance and potential combat operations. Designed for endurance and harsh conditions, it can operate for weeks and integrate with NATO naval systems via Stark’s Minerva software. The project aims to reduce reliance on crewed ships while addressing security concerns over maritime trade routes and critical infrastructure.
165CNA2026-11-03
MP Lee Hui Ying highlighted the need for Singapore to regulate autonomous vessels by balancing human oversight with accountability for safety and environmental risks. She questioned how the Ministry of Transport will align local laws with the International Maritime Organization’s evolving standards for autonomous ships. Lee also emphasized ensuring legal responsibility in accidents while maintaining fairness and transparency for businesses. The discussion took place during the Maritime and Port Authority of Singapore (Amendment) Bill debate.
166openalex2026-10-06Dionisis Kalogeropoulos, Georgia Sovatzidi, Panagiotis G. Kalozoumis, Δημήτρης Κ. ΙακωβίδηςDOI ↗ (opens in a new tab) This paper reviews AI and machine learning technologies for explainable failure prediction and prevention in maritime systems, addressing challenges in safety and reliability. It proposes a conceptual architecture combining data acquisition, anomaly detection, risk assessment, and explainable AI to support autonomous or human-in-the-loop interventions. The study analyzes existing maritime research, noting limitations in data availability, model generalization, and operational deployment. Key challenges include improving robustness, explainability, and trust in AI-assisted maritime decision-making.
This study examines ship safety in Indonesia by analyzing crew competence, port digitalization, and ship technology innovation. Using a systematic literature review of 50 articles (2021–2026), it finds these factors significantly improve safety outcomes like seaworthiness and risk control. The research relies on qualitative methods, including data reduction and thematic analysis. Limitations include the absence of direct quantitative statistical validation.
This scoping review analyzed 51 studies on team cognition in remote maritime operations, identifying five key themes: situation awareness, team learning, human-autonomy collaboration, interface design, and distributed cognition. Findings show a shift from individual to dynamic, interaction-driven models of team cognition involving humans, technology, and environmental factors. Challenges include integrating autonomous systems, improving interface design for shared understanding, and measuring team cognition effectively. The study recommends aligning design, training, and regulations with distributed cognition principles to enhance safety in remote maritime settings.
This paper reviews technologies and challenges for autonomous Crew Transfer Vessels (CTVs) and Service Operation Vessels (SOVs) in offshore wind farms. It highlights gaps in current manual operations, limited validation of autonomous systems, and the potential for improved efficiency, safety, and cost reduction. Key advancements in sensors, automation, and risk assessment are discussed, along with operational hurdles. The authors outline research priorities to advance autonomous vessel development.
The paper explores how unmanned surface vessels (USVs) can serve as forensic evidence in criminal cases due to their autonomous operation, remote control capabilities, and capacity to carry explosives discreetly. It highlights the unique challenges posed by their design, such as long-range control and stealth, in criminal investigations. The authors analyze methods for extracting forensically relevant data from USVs and their technical systems. The focus is on leveraging these features for law enforcement and forensic examination.
This study explores ethical concerns in human-AI interactions within maritime decision-making, based on focus groups with 30 experts from port management, nautical, and marine engineering fields. Key themes identified include trust in AI, accountability gaps, human override practices, and generational differences in ethical perspectives. Deck Nautical experts prioritized human control, while port management experts were more accepting of AI support. Experts agreed that younger, digitally native professionals may shift away from human-primacy values, posing unprepared institutional challenges.
This paper reviews digital twin (DT) applications in marine robotics, covering AUVs, ROVs, USVs, underwater gliders, and emerging platforms. A structured search analyzed 107 studies, identifying varied architectures, technologies, and validation methods but no fully operational deployments. Key challenges include balancing model fidelity with computation, environmental uncertainties, and communication limitations. The authors suggest physics-informed learning and edge computing as potential solutions but highlight the need for sustained, interoperable physical-virtual integration.
The paper introduces AETHELIS, an operational ecosystem for Governed Autonomous Infrastructure (GAI), addressing the shift from model-centric AI to infrastructure-driven autonomous systems. It integrates governance, adaptation, simulation, and orchestration into four layers: Sentinel (runtime control), ARL (self-improvement), Synapsis (simulation-based intelligence), and AEGIS (execution orchestration). The work proposes concepts like Governance Drift and the Constitutional Substrate to ensure long-term stability, accountability, and verifiable governance. AETHELIS is presented as a deployable architecture for governing autonomous intelligence and its evolution.
The paper presents Governed Autonomous Infrastructure (GAI) as a new framework for managing advanced autonomous AI systems. GAI consists of four layers: Sentinel System for oversight, Adaptive Research Layer for self-improvement, Synapsis Lab for testing, and AEGIS for operational control. It emphasizes infrastructure-based governance to ensure persistent oversight, safety, and controlled adaptation. The approach aims to support future AI development in areas like multi-agent coordination and robotics.
175Smart Maritime Network2026-11-06
DP World will partner with SHIFFT, a Dubai Future Foundation-led joint venture, to develop autonomous logistics systems for ports and industrial zones, starting at Jebel Ali Port. The collaboration aims to integrate autonomous vehicles into operations, focusing on safety, fleet management, traffic control, and digital twin technologies across DP World’s global network of over 60 ports. The initiative, supported by autonomous vehicle firm Oxa, seeks to enhance supply chain reliability and workforce skills while improving operational efficiency. Dubai’s Research, Development and Innovation Programme will oversee the project, targeting scalable solutions for global deployment.
176Naval Today2026-11-05
STARK unveiled the Vanta 24, a 24-meter uncrewed surface vessel (USV) designed for combat and maritime security in the Baltic Sea and Northern European waters. The USV can operate independently or alongside naval vessels, carrying up to 50 tonnes of payload, including anti-ship missiles, a 30 mm gun, and long-range radar, with speeds over 35 knots. It is built to endure harsh Baltic conditions and perform missions like escorting warships, monitoring suspicious shipping, and protecting underwater infrastructure. The vessel is part of STARK’s Vanta family, controllable via Minerva software, and aligns with NATO’s hybrid navy concept to enhance naval capabilities while reducing crew needs.
177ProtoThema2026-10-29
A Greek-owned ship in the Black Sea was struck by a maritime drone and sank on October 29, 2026. Video footage shows the attack, which did not result in any crew casualties. The incident highlights ongoing security risks in the region. The crew was reported safe.
178HuffPost Greece2026-10-29
A Greek-owned ship sank off the coast of Bulgaria in the Black Sea after being struck by a maritime drone. The incident was captured on video, showing the moment of impact. The article, published by HuffPost Greece, provides footage of the attack. No further details on casualties or the drone's origin are mentioned.
179bairdmaritime2026-10-28
The NTSB issued six safety recommendations after a 2024 collision in Lake Erie between a recreational motor yacht and a NOAA-operated uncrewed surface vessel (USV). The incident caused minor injury to the yacht operator and significant damage to both vessels, with the USV deemed a total loss. The NTSB attributed the collision to the USV's low visibility, lack of active monitoring, and insufficient autonomy safeguards. Recommendations include developing national USV standards for detectability, collision avoidance, and navigational safety, as well as design improvements by the manufacturer.
180gCaptain2026-10-27
The National Transportation Safety Board (NTSB) is urging new regulations for uncrewed vessels following a collision in Lake Erie. The incident prompted concerns about safety and operational standards for autonomous ships. The NTSB recommends stricter oversight to prevent future accidents. No specific rules were detailed in the report.
The paper examines the growing use of AI-driven Autonomous Weapons Systems (AWS) in military operations, highlighting gaps in adapting International Humanitarian Law (IHL) to these technologies. It proposes Meaningful Human Control (MHC) as a necessary framework, particularly for Lethal Autonomous Weapons Systems (LAWS). The study explores Artificial Moral Agents (AMA) as a potential solution to address challenges in applying IHL to AWS. A conceptual framework for integrating AMA into AWS is investigated.
182Marine Insight2026-10-14
The US Navy installed the DRAKE counter-drone system on the USS Ohio, an Ohio-class guided-missile submarine, to detect and jam small unmanned aircraft during surface operations. The system uses electronic warfare to disrupt drone communications, preventing remote control, but is ineffective against autonomous drones. Northrop Grumman is updating DRAKE with an Android-based interface and software-defined radio, based on field feedback. While the system provides an additional defensive tool, its detection and jamming ranges remain undisclosed, and it does not guarantee protection against all drone types.
StableAgent evaluates the behavioral consistency of autonomous software-engineering agents by testing their responses to differently worded but semantically identical issues. It modifies SWE-bench Lite issues using meaning-preserving transformations, then compares outcomes and patches between original and variant inputs. The tool includes a Streamlit GUI, CLI, and replay mode to replicate the ICSE 2027 pilot study without requiring an API key. Its goal is to measure whether agents produce stable results despite variations in issue descriptions.
The paper introduces FuzzyCS-Proto, a federated learning framework for classifying underwater ship structural surface conditions, addressing challenges like non-IID data, image degradation, and class imbalance. It uses fuzzy client selection based on reliability metrics (validation performance, uncertainty, image quality, and class balance) and class-wise prototype learning to improve cross-client alignment. Tested on a dataset with five classes (corrosion, defect, marine growth, normal surface, and paint peel), FuzzyCS-Proto outperforms baselines like FedAvg and FedProx, achieving Macro-F1 scores of 0.6501, 0.6292, 0.6641, and 0.5074 across four federated settings. Ablation and sensitivity analyses confirm the method’s effectiveness and interpretability.
This paper introduces an adaptive path planning algorithm for unmanned surface vehicles (USVs) to improve navigation in dynamic maritime settings. The method combines an enhanced ant colony optimization (ACO) algorithm—using a pheromone penalty mechanism and path smoothing—with a modified dynamic window approach (DWA) that optimizes overshoot, selection efficiency, and adaptive weight adjustments. Simulations show the approach reduces travel length and improves collision avoidance compared to existing methods. The result is more reliable navigation in complex marine environments.
186openalex2026-09-03Muhammad Fadhli Makhtar, Mohd Nizam Ab Rahman, Iliani Mohd Ikram, Mohd Hafiz Abdul Majid +2 moreDOI ↗ (opens in a new tab) This study designed and deployed the AtoN Remote Monitoring System (ARMS) in the Strait of Malacca to improve monitoring of marine aids to navigation in high-traffic waters. The system uses multi-sensor technology, hybrid communication (AIS, VHF, cellular), and a central platform, achieving 98.3% monthly availability and 98.7% communication success over a 90-day test across 478 installations. Fault detection was significantly faster (8.4 minutes) than traditional methods (15–45 days), with a 93.9% alarm accuracy rate. Results confirm the system’s effectiveness for real-time, condition-based management of maritime infrastructure.
This paper introduces an Agentic AI system for marine vessel condition monitoring and predictive maintenance. It combines a Transformer-based Autoencoder for anomaly detection with a Large Language Model (LLM) to provide explainable, interactive analysis. The system processes high-frequency operational data to identify issues like abnormal loading or equipment degradation, using structured tool-calling to reduce errors. Tested on 91 days of vessel data, it successfully detected four fault scenarios with lead times of 97 to 637 minutes.
This paper examines the progression of surgical robotics from basic mechanical systems in the 1980s to current platforms capable of interpreting tissue, regulating force, and performing tasks with minimal human input. It highlights key advancements like computer vision, force sensing, and machine learning that enable autonomy in procedures such as soft tissue manipulation and suturing. The authors address challenges like regulatory approval, ethical concerns, and training data quality as barriers to wider adoption. Future directions and their impact on surgical training, healthcare systems, and patient outcomes are also discussed.
This study examines how ergonomic flaws in navigational instruments, particularly ECDIS and INS, contribute to human error in maritime accidents. Researchers use eye-tracking technology in a full-mission simulator to analyze navigators' visual behavior under different lighting conditions and tasks. The project compares expert and novice strategies and aims to identify critical interface issues affecting cognitive workload and decision-making. Findings will inform design improvements, training standards, and theoretical understanding of digital interface impacts on maritime safety.
This paper presents a framework for certifying the safety of autonomous inland vessels by integrating sensor availability, perception reliability, and adaptive control. It uses a pre-computed lookup table to manage degraded sensors, reducing computational load while ensuring predictable behavior. The approach combines redundancy, reliability validation, and risk-based control to support safe navigation under varying conditions. The method aims to meet certification requirements for autonomous systems.
This paper addresses cybersecurity threats to unmanned surface vehicles (USVs), focusing on false data injection (FDI) attacks that disrupt sensor data or communications. It introduces an adaptive control scheme with an adaptive threshold event-triggering mechanism (ATETM) to maintain stability and reduce communication demands. Novel coordinate transformations and the Nssbuam function help counteract time-varying attack effects. Simulations confirm the method achieves accurate path tracking while lowering control update frequency under deception attacks.
192Splash2472026-11-04
The *Seafarers Happiness Index* reports a decline in seafarer satisfaction, dropping to 6.81/10 in Q3 2026, with workload, connectivity, and shore leave as key frustrations. Crews rely on camaraderie to cope with systemic shortcomings, but compressed work demands and denied shore leave push human endurance beyond sustainable limits. The article argues that shipping treats seafarer resilience as an assumed resource rather than a finite capacity, risking burnout. Technology and efficiency gains must reduce pressure on crews, not intensify it, to prevent normalizing overload.
This study examines how strict procedures and automation in modern ship operations may limit seafarers' exposure to unexpected situations, reducing their emergency readiness. A survey of 100 seafarers and trainees in Indonesia found that less experience with abnormal events correlates with lower preparedness for emergencies. The research suggests that realistic training and varied scenarios could enhance maritime safety. Statistical analysis confirmed the link between exception exposure deprivation and vulnerability in emergency response.
The paper introduces the Governance-Centric AI Framework for Enterprise Production Readiness (GAEPR), addressing gaps in assessing software readiness for production. GAEPR combines rule-based checks and AI to evaluate architecture, runtime behavior, infrastructure, deployment, observability, and resilience. It includes a Production Readiness Index (PRI) to provide a single, explainable score for operational readiness. The framework maintains human control over final decisions while using AI for interpretation in a controlled enterprise scenario.
This study introduces a framework combining BERTopic and Contrimetric methods to analyze topic trends and impact in smart ship technology. It uses semantic modeling, logistic growth curves, and thematic clustering to track technological life cycles and knowledge diffusion. The approach identifies research hotspot shifts and developmental pathways in the field. Results offer insights for researchers, businesses, and policymakers to support innovation and sustainability in the smart ship industry.
The study introduces a data-driven framework combining Bayesian networks (BN) and TOPSIS to analyze and mitigate piracy risks in the Strait of Malacca. Key risk factors like "ship area boarded" and "crew response" were identified, with ship-level interventions proving more effective than broader measures like joint patrols. Despite existing measures, the model estimates a 57% probability of successful piracy, underscoring the need for improved strategies. The framework offers policymakers a quantitative tool for prioritizing anti-piracy actions, though it currently excludes socio-political factors and is tailored to Southeast Asia.
197shippingtelegraph2026-11-04
Singapore highlighted risks from emerging maritime technologies like AI and autonomous ships, which could improve navigation but also enable cyber threats and disruptions to critical underwater infrastructure. Minister Edwin Tong warned that drones, autonomous vessels, and cyber-attacks may compromise ship safety, port operations, or unlawfully seize vessels. The statement, delivered for Fiji, Jamaica, Malta, and Singapore, supported a mandatory framework for autonomous ships while stressing the need for accountability and safeguards. It also condemned unlawful transit restrictions in key straits, citing global economic risks.
This paper presents a control method for coordinating multiple unmanned surface vehicles (USVs) to maintain formation while tracking a virtual leader. The approach addresses challenges like unknown, changing environmental disturbances and actuator limits using a disturbance observer and dynamic compensation. Stability is confirmed through Lyapunov analysis, and simulations validate the method’s effectiveness in handling disturbances and input saturation. The system ensures obstacle avoidance while preserving formation geometry.
This paper presents a fault-tolerant control (FTC) method for unmanned surface vessel (USV) formations, addressing challenges like underactuation, environmental disturbances, and communication link failures. The approach uses head nodes for command dissemination and a virtual leader to generate reference trajectories, improving robustness. An adaptive state observer and backstepping-based controller compensate for actuator and communication faults in real time. Simulations show the method reduces steady-state errors to 10⁻⁴ meters and enhances fault resilience compared to non-FTC approaches.
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.
201Foro3D2026-06-30
A 2026 autonomous catamaran was wrecked after colliding with underwater debris, which damaged its composite rudder. The incident highlights vulnerabilities in the vessel’s design and navigation systems. No further details on casualties or environmental impact were provided. The failure raises concerns about the reliability of autonomous maritime technology in real-world conditions.
This paper analyzes current methods for planning maritime Aids to Navigation (AtoNs), finding them fragmented across scientific studies, IALA guidelines, and national laws. Scientific tools are partial, IALA offers broad standards but lacks site-specific procedures, and legal frameworks define roles without clear, reproducible placement methods. The authors propose an integrated framework covering spatial, operational, and technological domains, demonstrated through a case study of a 2024 Adriatic Sea grounding. The framework aims to improve risk-informed decision-making but remains conceptual, requiring further development and validation.
This paper examines how the EU AI Act applies to AI systems used in Earth Observation (EO), focusing on its risk-based framework. It analyzes EO use cases in areas like law enforcement, migration, and infrastructure, showing that an AI system’s risk classification depends on its purpose, autonomy, and context. While most current EO AI systems are not yet deemed high-risk, the authors warn this may change as technology advances. The study calls for EO researchers to adopt responsible AI practices, including explainability and risk assessment, to align with regulatory demands.
This paper examines the shift from human-controlled industrial systems to AI-driven autonomous decision-making. It combines two frameworks to analyze how human expertise transfers to AI systems, introducing new failure risks like model errors and context blindness. Evidence from aviation, manufacturing, and other sectors shows automation erodes tacit human skills, leading to irreversible knowledge loss. The authors propose a safety framework emphasizing human oversight and updated regulations for AI-integrated industries.
205safety4sea2026-04-23
DNV and the Singapore Institute of Technology (SIT) have partnered to advance research on autonomous maritime operations. The collaboration aims to develop technologies and frameworks supporting safe and efficient autonomous shipping. This initiative focuses on innovation in maritime safety and operational standards. The agreement was announced on April 23, 2026.
206강원도민일보2026-11-08
The *Tamnara-ho*, a passenger ship operated by Namisum, became South Korea’s first domestic vessel to receive approval for its autonomous operation safety assessment. The certification confirms the ship meets safety standards for unmanned or partially automated navigation. This milestone reflects progress in integrating autonomous technology into maritime transport. The assessment was conducted under domestic regulatory frameworks.
207연합뉴스2026-11-08
The passenger ship *Tamnara-ho* operating near Namisum Island in Chuncheon has been approved for an autonomous operation safety assessment. This marks a step toward evaluating the vessel's capability for self-navigation. The approval was announced by Yonhap News on November 8, 2026. No further details on the assessment timeline or process were provided.
208美国之音中文网2026-11-07美国之音
Taiwan intercepted four Chinese coast guard vessels intruding into Kinmen waters on November 6. To counter China’s maritime gray-zone harassment, Taiwan is investing in asymmetric unmanned boat technology, showcasing systems like STR8 Industries’ *Ghostwake* and MARTAC’s *Devil Ray T24* at its first maritime unmanned systems expo. Officials and experts emphasized the need for AI, indigenous defense tech, and unmanned systems to improve surveillance, reduce risks to personnel, and enhance operational flexibility. Taiwan asserts China’s actions violate international law and aims to deploy scalable, cost-effective unmanned platforms for defense.
209브릿지경제2026-11-06
South Korea's first autonomously operated passenger ferry, the Naminara Republic ferry (탐나라호), has been approved for safety evaluation. This marks the first time a domestic passenger ship will undergo assessment for autonomous operation. The approval signifies a step toward advancing autonomous maritime technology in the country. The ferry's safety evaluation process will determine its readiness for autonomous navigation.
210MarketScale2026-11-06
Burq introduced *Earned Autonomy*, a framework where delivery AI starts with no control and gradually gains authority per shipping mode (e.g., fleet, gig, parcel, LTL, drones) based on live-order performance, such as 90% dispatcher agreement. Retailers set trust thresholds, and AI is automatically demoted if it breaches hard rules, ensuring gradual, evidence-based autonomy. The system tracks decisions in a *Decision Ledger*, recording each order’s outcome, but lacks pre-live performance metrics. Burq’s approach contrasts with "human in the loop" models, treating dispatchers as temporary validators rather than permanent overseers.
211北海道新聞デジタル2026-11-03
Tsuneishi Solutions Tokyo Bay obtained ClassNK technical certification for its autonomous navigation technologies, "sMCS" and "iRPS." The certification confirms compliance with industry standards for these systems. The technologies aim to enhance ship navigation and operational safety. The announcement was made on November 3, 2026.
212搜狐网2026-10-31
A French aircraft detected and warned NATO forces 40 minutes in advance about approaching unmanned boats, but Bulgaria failed to intercept them. The incident left NATO in a vulnerable position, highlighting gaps in regional defense coordination. The article suggests the unmanned vessels posed a significant threat despite early detection. No further operational details or outcomes were provided.
213ライブドアニュース2026-10-30
Tsuneishi Solutions Tokyo Bay received ClassNK’s technical certification (TQ) for its autonomous navigation technologies, "sMCS" and "iRPS," on October 30, 2026. The certification recognizes the technical reliability of these systems. "sMCS" and "iRPS" are designed to support autonomous ship operations. The news was reported by Livedoor News.
214沖縄タイムス社2026-10-30
Tsuneishi Solutions Tokyo Bay received ClassNK’s technical certification (TQ) for its autonomous navigation technologies, "sMCS" and "iRPS." The certification recognizes the systems' compliance with industry standards for maritime safety and performance. These technologies aim to enhance ship navigation through automation. The achievement was reported by Okinawa Times on October 30, 2026.
215Yahoo!ニュース2026-10-29
On October 29, 2026, a container ship in the Black Sea was attacked by an unmanned boat. The Bulgarian navy successfully rescued all crew members from the vessel. The incident highlights ongoing security concerns in the region. No further details on casualties or the attackers were provided.
216Yahoo!ニュース2026-10-29
On October 29, 2026, a container ship in the Black Sea was attacked by an unmanned boat. The Bulgarian navy successfully rescued all crew members from the vessel. The incident occurred amid heightened maritime tensions in the region. No further details on casualties or the origin of the attack were provided.
217Marine Insight2026-10-28
The U.S. Navy will equip five Arleigh Burke-class destroyers with Applied Intuition’s $25 million AI-powered Intelligent Perception System (IPS) to enhance vessel detection. The system integrates infrared sensors, cameras, and navigation feeds to automatically identify, track, and predict maritime threats in real time, reducing human error risks. IPS processes data onboard using edge computing and logs ship traffic digitally for faster analysis and fleet-wide intelligence sharing. It also supports machine learning model updates by transmitting sensor data to shore stations when bandwidth permits.
218財経新聞2026-10-21
HD Hyundai and Anduril demonstrated autonomous operation of an unmanned vessel off the U.S. coast in October 2026. The test included the vessel's ability to respond to an engine failure. The trial showcased advanced autonomous navigation and system resilience. No further technical details or outcomes were specified.
219Yahoo!ニュース2026-10-15
The Japan Coast Guard conducted a training exercise in Miyagi Prefecture’s Shiogama Port on October 15, 2026. The drill involved using remote-controlled unmanned boats designed to detect hazardous substances in the water. The training aimed to enhance response capabilities for potential maritime threats. No specific outcomes or results were reported.
This paper introduces a method to translate maritime safety regulations (COLREGs) from a structured language (Legata) into verifiable logical properties using a four-stage pipeline. The process relies on LLM agents (GPT-4o) for initial stages, with expert oversight and model checking (Rebeca) for verification. Evaluations show improved accuracy with a "skillful" LLM configuration, achieving higher scores in syntax, coverage, and logical completeness. The work provides a reusable pipeline, evaluation metric, and insights into regulatory clauses suitable for actor-based model checking.
221Yahoo!ニュース2026-10-05
The article discusses Japan’s Self-Defense Forces' research on autonomous ships. Key focus areas include improving navigation safety, reducing human error, and enhancing operational efficiency. The development aims to integrate advanced technologies for unmanned or remotely controlled vessels. Public and expert opinions on priorities and challenges are also highlighted.
222搜狐网2026-10-05
A 2026 deal for 30 U.S. military unmanned boats revealed significant operational issues, including collisions and loss of control. The problems exposed in the program highlight persistent technical and reliability challenges. Reports indicate a range of malfunctions undermined the boats' intended functionality. The article critiques the contrast between expectations and actual performance.
223乗りものニュース2026-10-03
The UK Royal Navy is advancing toward unmanned underwater warfare with its extra-large unmanned surface vessel (USV) testing the capability to fire U.S.-made torpedoes. This development signals a shift toward integrating autonomous systems in naval combat operations. The move highlights growing collaboration between the UK and U.S. in modernizing maritime defense technology. Unmanned systems may play a larger role in future underwater warfare strategies.
224世界新聞網2026-10-03
The U.S. plans to expand the use of faster and lower-cost unmanned surface vessels (USVs) to combat smuggling and drug trafficking. These vessels are intended to improve efficiency and reduce operational expenses. The initiative aims to enhance maritime security and deterrence efforts. No specific implementation details or outcomes were provided.
225FETV2026-10-01
Samsung Heavy Industries, currently ranked lower in shipbuilding competitiveness, is focusing on autonomous navigation and robotic factories to improve its position. The company aims to enhance efficiency and innovation by integrating advanced technologies. This strategy targets long-term competitiveness in the global shipbuilding market. The approach contrasts with traditional methods used by higher-ranked competitors.
This study presents a combined procedure using heavy-class ROVs and manned diving to enhance safety and efficiency in underwater search and rescue during large marine disasters. It analyzes tidal-current impacts and operational limits, finding ROV-SSDS integration allows longer diving windows than ROV-SCUBA due to SCUBA’s stricter current restrictions. The procedure incorporates ROV-mounted sensors for situational awareness, target localization, and safety monitoring. A classification framework was also developed to guide the selection of ROV-only, manned-diving-only, or integrated operations based on disaster severity, vessel needs, and depth.
This study introduces a new model combining AcciMap and graph convolutional networks (GCN) to analyze causes of maritime accidents in the Yangtze River waterway. The model uses mutual information, a grey wolf optimizer, dropout layers, and weakly supervised learning to identify causal chains and rank accident causes by importance. It outperformed baseline models, achieving an MAE of 0.0820 and RMSE of 0.1694, with faster training convergence. The findings offer insights for improving maritime safety strategies and sustainable waterway transportation.
228Hellenic Shipping News2026-11-03
KONGSBERG expanded its Aegir SSA sonar family with two new models, Aegir17 and Aegir57N, now available for order alongside the existing Aegir57. Aegir17 offers long-range, 360-degree detection for larger platforms, while Aegir57N provides compact, high-definition navigation and security for unmanned vessels and fixed installations. The company also partnered with Viam to develop an AI-powered virtual sonar operator to automate underwater object detection. The Aegir SSA family integrates with broader maritime surveillance systems for enhanced subsea and surface monitoring.
229designdevelopmenttoday2026-11-03
The NTSB recommended that an autonomous boat manufacturer modify its design following a collision. It also advised NOAA to update its policies to ensure uncrewed surface vessels (USVs) are detectable by other operators. The recommendations include requiring testing to verify vessel detectability. The changes aim to improve safety in maritime operations.
This paper presents an AI-based framework for quickly evaluating the hydrodynamic performance of deformed marine structures like ships and offshore platforms. The method uses multi-view images to reconstruct a 3D model via the HunYuan3D model, followed by numerical simulations to assess stability and motion responses. Validation on a deformed ship showed geometric parameter errors under 3% and results consistent with known damage effects. The approach offers a low-cost, efficient, and reliable tool for emergency decision-making in maintenance and safety planning.
This study examines whether rankings of materials (e.g., for band gaps or alloy formation energies) remain consistent across different data sources, despite discrepancies in absolute values. Using a method called PEGKi, researchers analyzed 261,053 band-gap records and Al–Mg–Si alloy simulations, finding that relative rankings often transfer reliably between sources, even when raw data does not. For alloys, the approach correctly identified the most stable interatomic potentials and rejected unreliable ones. The findings suggest that reusing prior knowledge based on relative performance can save computational and experimental resources.
This paper introduces a trajectory planning method for autonomous surface vehicles that doesn’t rely on pre-set guide paths. It combines model predictive control (MPC) with a turning circle-based control barrier function (TC-CBF), which considers the vehicle’s turning ability and nonholonomic motion. The approach creates distinct left- and right-turning avoidance modes, improving success rates and reducing safety violations in dynamic environments. Simulations show it outperforms single-mode methods in traffic-heavy scenarios.
This paper addresses fault-tolerant control for underactuated unmanned surface vessels (USVs) with rotatable thrusters experiencing thruster faults. It introduces a dynamic compensation controller to manage input constraints and allocation errors, improving accuracy and convergence speed. A multi-channel event-triggered mechanism reduces unnecessary updates, saving network bandwidth, while a finite-time disturbance observer estimates faults and external disturbances. Theoretical analysis and simulations confirm the method’s stability and efficiency in fault compensation and communication.
234crossref2026-05-27Reno Aditya Hendriantoro, Capt. Firdaus Sitepu, Dian Junita Arisusanty, I'ie SuwondoDOI ↗ (opens in a new tab) This study examines ship management in Indonesia’s narrow channels, focusing on the Amamapare Channel, where accidents rise due to larger ships, logistics demands, and hydrodynamic issues like bank effect and squat. Researchers analyzed the MV Meratus Dili’s voyages, interviewing officers and observing operations, finding speeds above 6 knots at low tide reduce Under Keel Clearance (UKC) by 0.35 meters. The optimal speed for safety is 4–5 knots during low tide or high traffic, maintaining a UKC of at least 0.5 meters. Improved standard operating procedures (SOPs), including checklists and training, could reduce accidents by 20–30%.
The paper analyzes how the 1992 International Convention on Civil Liability for Oil Pollution Damage applies to remotely operated ships, focusing on the liability of remote operators. The IMO is considering whether to extend the convention’s "channelling of liability" provision—which limits negligence claims against certain parties—to include remote operators. Leaving their status undefined risks legal uncertainty, while explicitly clarifying it could either simplify liability or weaken environmental protections. The article evaluates both approaches, weighing treaty interpretation, case law, and policy implications.
236Marine Insight2026-11-06
France has extended its Atlantique 2 maritime patrol aircraft deployment in Romania due to rising attacks on merchant ships in the Black Sea. The aircraft, initially sent on October 18, will remain for additional weeks to monitor threats like sea drones and support commercial vessel safety. In October, nine ships were struck near Romania and Bulgaria, resulting in 34 seafarers dead or missing. While the aircraft can detect and warn of threats, it lacks the capability to intercept or neutralize them.
237Pulse 2.02026-11-06
Windward, a maritime AI company, acquired Azimut.ai to enhance its vessel monitoring capabilities using optical sensors. This expands Windward’s platform by adding ground- and ship-based visual intelligence, improving detection of vessels that evade traditional tracking signals like AIS. The technology creates digital vessel fingerprints without raw imagery, integrating with existing data to assess risks and support maritime security. The acquisition strengthens Windward’s proprietary data collection and aims to provide more accurate, independent verification of maritime activity.
238Marine Technology News2026-11-05
Equinor opened the K-lab Marine Robotics Centre (KNARR) at Norway’s Kårstø processing plant in October 2026 to test underwater robots, autonomous vessels, and related technologies for offshore operations. The facility, connected to an active plant, offers three testing areas at depths of 25, 140, and 250 meters, along with subsea cables and infrastructure for long-term sensor and drone testing. Funded with $1.73 million, the center aims to cut operational costs by hundreds of millions of kroner annually by improving efficiency and reducing reliance on larger vessels. It will support collaboration among industry partners, research institutions, and suppliers to advance autonomous offshore maintenance and monitoring.
239National Defense Magazine2026-10-27
The U.S. Navy is adjusting its approach to uncrewed systems due to lessons from the Iran conflict. It is now prioritizing sustainment—ensuring long-term maintenance and logistics—and electronic warfare (EW) capabilities. These changes aim to improve reliability and resilience in contested environments. The war has highlighted gaps in current uncrewed system strategies.
240Splash2472026-10-07
The Aframax Rio, a Liberia-flagged tanker linked to Russian oil exports, caught fire off Sochi after an attack by unmanned surface vessels, causing an oil spill but no crew injuries. The incident highlights escalating threats in the Black Sea, with three merchant vessels struck in NATO members Romania and Bulgaria’s exclusive economic zones within 24 hours. Attacks on Danube River ports, now a critical export route for Ukraine, have surged as cargo shifts from targeted Odesa-area ports, with strikes increasing 3.7 times since July. Congestion and rising insurance costs further strain maritime trade, as security risks expand across the region.
This study proposes a machine learning-based method to diagnose and restore faulty signals in ship structure monitoring systems, combining wavelet transform, IPSO-BP neural networks, CNNs, and adaptive algorithms. Tested on model monitoring data, the method achieved over 98% diagnostic accuracy across different ship positions and outperformed LSTM and Random Forest in noise resistance. It also significantly improved signal restoration, reducing RMSE by up to 75.49% for drift faults compared to traditional methods. The approach aims to enhance the stability and safety of ship structural health monitoring.
242Marine Insight2026-09-19
A U.S. naval operation nearly intercepted a Chinese ship in the Middle East due to an AI-assisted intelligence error in 2026. The mistake was identified and corrected after senior analysts and experts reviewed the data. The incident highlights risks in relying on AI-driven intelligence without human oversight. No boarding occurred following the reassessment.
The *Claude Code Complete User Handbook* by David Soldani (2026) outlines best practices for safely operating Claude Code, an agentic work environment with filesystem access, shell execution, and multi-agent orchestration. It identifies systemic failure risks—such as unreviewed hooks or over-scoped connectors—and emphasizes four key principles: defining completion conditions, separating control layers, treating third-party tools as supply-chain dependencies, and trusting observed evidence over agent statements. The book includes 34 chapters covering installation, governance, and verification, with citations for all claims and an evidence ledger for corrections. It also maps controls to external frameworks and proposes an adoption maturity model, labeling unverified claims explicitly.
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.
This paper proposes an adaptive neural network-based control method for unmanned surface vessels (USVs) to track trajectories despite false data injection (FDI) attacks, system uncertainties, and disturbances. It introduces a dual-channel dynamic event-triggered mechanism (DDETM) to reduce communication overhead and actuator wear while enabling thrust allocation. The approach uses a second-order prescribed performance function (SOPPF) and dynamic surface control (DSC) to maintain tracking accuracy and simplify computations. Simulations confirm the method’s effectiveness in ensuring stable and bounded system performance.
246openalex2026-05-11Hector Woods, Philippa Ryan, Rob Alexander
This paper explores how the geometric properties of ReLU neural networks can improve interpretability for autonomous systems. It highlights that current explainable AI methods often rely on simplified models, which lose accuracy and may not reflect the original network’s decisions. The authors demonstrate that ReLU networks divide input space into linear regions, enabling direct extraction of causal explanations without performance loss. This approach aims to provide reliable "why" and "why not" explanations while maintaining the network’s original behavior.
This paper discusses the need for hydraulic intervention in oil and gas wells, which uses chemicals or fluids under pressure for maintenance, remediation, or stimulation. It highlights the challenges of delivering fluids to subsea wells, requiring dedicated intervention vessels with remotely operated vehicles (ROVs) and specialized equipment like a subsea safety module (SSM). The SSM, as per API recommended practice 17G2, provides isolation valves, downline connection points, and an injection connection point for safe well intervention. Fluids can be injected at various locations, such as the subsea Christmas Tree or retrievable choke, depending on access availability.
248SAFETY4SEA2026-11-05
The shipping industry’s digital transformation is expanding cyber risks as interconnected systems integrate navigation, machinery monitoring, and cargo operations. While new regulations and AI-driven tools aim to strengthen cybersecurity, concerns persist about whether resilience is keeping pace with technological complexity. Smaller operators and third-party dependencies create vulnerabilities, and operational technology—critical for vessel safety—requires tailored security measures. Recent data show rising cyber incidents, with phishing and operational tech exposure as key threats, while regulatory shifts emphasize implementation and lifecycle management over mere compliance.
249Defense News2026-11-03
France launched a defense industry "pact" to accelerate the development of naval drones tailored to its navy’s needs, announced by Minister Catherine Vautrin at the Euronaval trade show. The initiative targets technologies for mine removal, seabed exploration, and oceanographic data collection, addressing gaps in underwater infrastructure security. Key acquisitions include a second deep-sea ROV drone, eight A18 countermine robots, and an expanded unmanned combat underwater vehicle. Additionally, France will upgrade its FDI frigates to carry 32 Aster interceptor missiles, doubling current capacity.
250Marine Insight2026-11-02
The U.S. Navy partnered with Gecko Robotics in a $300 million deal to deploy AI-powered wall-climbing robots for ship hull inspections, claiming they can complete the process 50 times faster than human teams. These robots detect cracks and corrosion with high-precision sensors, reducing maintenance time from months to days and cutting repair costs by about $8 million per vessel. The Komodo system scans surfaces without removing paint, using ultrasonic waves to inspect through coatings and metal plating. The Navy aims to boost fleet readiness to 80% by 2027, with future underwater-capable robots (Axoloti) in development for full inspections without drydocking.
251Sea News2026-10-12
The article discusses the importance of integrating safety into the design of uncrewed maritime systems. It emphasizes that the growing adoption of autonomous ships requires a "safe by design" approach to prevent accidents and ensure reliability. The maritime industry must prioritize safety standards to support the uncrewed revolution. Regulatory frameworks and technological safeguards are critical for long-term success.
252Fortune Business Insights2026-09-21
The AI-Based Vessel Traffic Management market is projected to grow significantly by 2034. The report by Fortune Business Insights analyzes market size, share, and trends. It focuses on advancements in AI technology improving maritime safety and efficiency. No specific data or growth figures are provided in the given text.
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.
254safety4sea2026-09-11
The 2026 MASS Code establishes mandatory safety and operational standards for Maritime Autonomous Surface Ships (MASS). It outlines requirements for risk assessment, cybersecurity, and human oversight to ensure compliance with international maritime regulations. Ship operators must adapt their procedures to meet these new guidelines, which aim to integrate autonomous vessels safely into existing maritime frameworks. The code applies to all MASS degrees, from partially to fully autonomous systems.
255Marine Technology News2026-08-15
The article discusses advancements in radar processing for maritime autonomy, focusing on how raw radar data is transformed into actionable decisions for safe navigation. It highlights the role of radar systems in improving situational awareness and collision avoidance for autonomous ships. The piece emphasizes the importance of real-time data interpretation to enhance safety in maritime operations. No specific methods or results are detailed beyond the general focus on radar-based decision-making.
This paper, Part II of a study by Dr. Osama Ellian, outlines proposed safety and technical rule requirements for well-stimulating ships handling acids. It focuses on measures to eliminate, prevent, and mitigate hazards related to acid transport and use in these vessels. The rules address ship design, installation, and operational preparedness for new constructions, retrofits, and existing ships. The guidance aims to assist regulators, operators, and stakeholders in managing risks associated with well-stimulating operations.
This paper examines modern approaches to training specialists in hydrometeorological and hydrographic support for navigation, emphasizing the need for updated education due to digitalization, stricter safety demands, and evolving maritime conditions. It highlights the shift toward an integrated, competence-based model combining hydrography, meteorology, oceanography, and geoinformation technologies, with a focus on digital tools, big data, and simulation training. The study compares Ukraine’s education system—strong in theory but needing more interdisciplinary and practical integration—with international standards. Key recommendations include adopting digital platforms, practice-oriented learning, and analytical skill development to improve decision-making in complex maritime environments.
258Marine Link2026-11-06
ShipIn Systems appointed Kunal Pathak as Vice President of Strategic Partnerships to strengthen collaborations with marine insurers, P&I clubs, and industry stakeholders. Pathak, a former Master Mariner with over 12 years at sea and experience in marine insurance and risk management, will focus on expanding the reach of ShipIn’s AI platform, FleetVision. His role aims to enhance loss prevention and risk assessment through real-time operational data, supporting closer ties between shipowners and insurers. FleetVision, deployed on over 1,300 vessels, provides continuous AI-driven insights to improve safety and operational performance.
259自由時報2026-10-14
The U.S. and Taiwan are collaborating to build a "non-red" military supply chain, excluding China, by producing unmanned vehicles like drones and boats. Since September 2025, at least 13 agreements have been signed, including a $1 billion drone deal with Anduril, while Taiwan plans to spend over $7 billion on drones in six years. The partnership follows a "you design, I manufacture" model, with Taiwan’s shipbuilder CSBC teaming up with U.S. firm HavocAI to develop autonomous naval systems. This effort aims to bolster Taiwan’s defense against China and supply equipment for U.S. forces abroad.
260Splash2472026-09-23
The 20-year-old containership *MSC Hermes III* was abandoned by its 25 crew in the South China Sea after issuing a distress alert on September 22. The vessel, now classified as a "derelict," is drifting near coordinates 11°45’N 112°15’E, about 300 km east of Vietnam, with no confirmed cause for the emergency or reports of injuries. Three ships, including *MSC Ruby*, responded to the alert, rescuing the crew, but the ship remains adrift without towage or salvage arrangements. Authorities have not disclosed details about the cargo, including container count or hazardous materials.
This paper introduces an adaptive fault-tolerant control method for underactuated unmanned surface vehicles (USVs) to maintain trajectory tracking despite actuator faults and external disturbances. The approach combines prescribed performance control, radial basis function neural networks, and barrier Lyapunov functions to keep tracking errors within set limits while addressing both multiplicative and additive faults. A smooth shifting function allows the controller to handle initial constraint violations, improving operational flexibility. Simulations show the controller achieves position errors below 0.04 m and yaw errors below 0.03 rad, even with 50% actuator degradation and multiple fault events.
This study analyzes the structural safety of a marine ROV launch and recovery system (LARS) under extreme sea conditions, focusing on its vulnerability to high-frequency impacts. Simulations revealed that traditional rigid frames face significant stress (195.38 MPa) and deformation (over 20 mm) under a 1 g horizontal impact. A viscoelastic damping solution was proposed, reducing peak stresses by over 37% and deformation by 64%. The approach offers a lightweight alternative to conventional strengthening methods for marine equipment.
263Business Wire2026-10-15
Fincantieri is speeding up the use of robotics and physical AI to modernize its shipyards. The company aims to create the "shipyard of the future" by integrating advanced technologies. This initiative focuses on improving efficiency and innovation in shipbuilding. No specific methods or outcomes are detailed in the provided text.
264Marine Insight2026-10-13
A U.S. Navy destroyer, USS Paul Ignatius, joined Sweden and Finland in a military exercise in the Baltic Sea and Gulf of Bothnia to enhance naval coordination and protect sea routes. The drills included live-fire targeting of uncrewed vessels and air-defense training, focusing on securing maritime trade lanes and critical infrastructure like undersea cables. Finnish and Swedish crews collaborated with U.S. personnel, sharing regional expertise to improve combat readiness in challenging conditions. The exercise highlighted NATO’s strengthened capabilities following Finland and Sweden’s recent alliance membership.
This study examines how the bank effect—hydrodynamic forces between a vessel and fairway banks—influences navigation safety for full-form vessels like tankers. Using a validated navigational simulator, researchers tested vessel trajectories near sloped banks at varying speeds and distances, comparing results with towing tank data. A polynomial regression model (accuracy: 0.9746) determined minimum safe distances, revealing sloped banks can pose greater grounding risks than vertical walls, especially when vessels sail over the slope. The findings highlight the need for situation-specific safety measures to reduce navigation risks.
This study evaluates the reliability of human-ship-environment interactions in maritime accidents using an AIS-based systems engineering approach. It highlights the importance of accurately interpreting vessel behavior influenced by human operations, ship dynamics, and environmental conditions. The paper emphasizes that Automatic Identification System (AIS) data offer critical technical support but may have limitations. The approach aims to improve accident reconstruction by integrating these factors systematically.
The second edition of *Maritime security and risk assessments* addresses evolving challenges in maritime safety, including digitization, automation, cyber-physical risks, and geopolitical threats. It expands on the first edition by exploring risk-informed decision-making, validation, and system resilience through three research streams: collision-risk sensing, human-technology interaction, and port safety. Studies use traffic data, simulations, and accident reports but face limitations like incomplete validation, sparse data, and weak cross-scale integration. Effective implementation requires trustworthy data, uncertainty management, human-centred assurance, and preparedness for cyber-physical and security failures.
This study introduces the STPA-Emergence framework to analyze system failures in Unmanned Surface Vessels (USVs) by focusing on risks from dynamic interactions in Human-Vessel-Environment (H-V-E) systems. It aims to overcome limitations of traditional safety methods, which often miss non-component risks. The approach combines System-Theoretic Process Analysis (STPA) with emergence theory to improve failure identification. The paper presents a coupling mechanism to better understand USV system vulnerabilities.
This paper introduces a framework to monitor maritime navigation integrity in fairways under GNSS jamming and spoofing threats. It combines AIS dead-reckoning with a GNSS RAIM baseline, using a two-state Hidden Markov Model (HMM) and a reinforcement-learning Deep Q-Network (DQN) to detect interference while maintaining low false alarms. The approach focuses on cross-track error (CTE) and protection bounds, improving detection rates—jamming (~93%) and spoofing (~99.5%)—compared to GNSS-only methods. Jammer/spoofer localization is also demonstrated, with accuracy ranging from meters to kilometers depending on geometry.
This paper proposes an automated framework for determining liability in accidents involving autonomous vehicles. It uses edge intelligence, machine learning, and graph theory to process real-time sensor data from vehicles, weather, and roadside units. The system constructs event identity graphs to map causal relationships and cross-references them with insurance codes, traffic laws, and ethical policies. The approach aims to improve transparency, fairness, and efficiency in liability assessments compared to traditional manual methods.
This paper examines the legal challenges posed by autonomous vehicles (AVs) in land, sea, and air transportation, where traditional fault-based liability frameworks struggle due to the shift from human to algorithmic control. It highlights the ambiguity in determining liable parties when control and benefit are separated. The authors propose a unified tort liability framework to address these issues. The study focuses on clarifying accountability in cross-modal autonomous transportation systems.
272openalex2026-08-03Elizabeth Dietrich, Hanna Krasowski, Emir Cem Gezer, Roger Skjetne +2 more
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.
273openalex2026-07-13R Ferreira da Silva, Milad Abolhasani, Peter Beaucage, Laura Biven +24 more
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.
The paper explores the potential of autonomous vehicles (AVs) to address road safety, congestion, and mobility issues in Nigeria. It highlights challenges such as weak infrastructure, regulatory gaps, and the need for context-specific analysis. The study emphasizes aligning AV adoption with Nigeria’s institutional, technological, and socio-cultural conditions. Limited existing evidence on AVs in African contexts is noted as a key concern.
This paper introduces an interpretable reinforcement learning framework for autonomous warehouse robots, combining deep reinforcement learning with explainability methods like saliency mapping and feature importance analysis. The approach improves transparency and trust by making the robot’s decision-making process understandable to operators. Experimental results showed a 98% collision rate in one outcome, while successful runs achieved faster navigation with an average time of 31.87 seconds and a path smoothness score of 0.539. The framework enhances efficiency and reliability for logistics and inventory management applications.
276openalex2026-05-26Yuhang Zhang, Shuqi Chai, Yukang Zhang, Liusha Yang +4 more
This paper introduces a reinforcement learning framework for safe USV navigation that accounts for perception uncertainty and compliance with maritime collision regulations (COLREGs). The method combines credibility-weighted learning to adjust for noisy sensor data, a geometric safety shield to prevent hazardous actions, and continuous rule-aware signals to smooth navigation decisions. The approach improves training stability and reduces collisions compared to existing methods. Simulations show better performance in dynamic environments with unreliable perception systems.
This paper by A. Dhyani (2026) presents a framework for safe autonomous vessel navigation in inland waterways under uncertain and abnormal conditions. It introduces a robust system identification method for vessel maneuvering models, a Nonlinear Model Predictive Control (NMPC) system for constraint-compliant navigation, and a sensor Fault Detection and Isolation (FDI) scheme to monitor and diagnose sensor faults. The study also proposes a risk mitigation approach using Bayesian Belief Networks and Partially Observable Markov Decision Processes to handle failures like collisions or grounding. Validation includes full-scale trials, simulations, and case studies demonstrating improved prediction accuracy, control performance, and fault resilience.
278openalex2026-04-22Harry Robertshaw, Nikola Fischer, Han‐Ru Wu, Andrea Walker Perez +5 more
This study explores a world-model-based reinforcement learning (RL) framework, TD-MPC2, for autonomous endovascular navigation in mechanical thrombectomy. Tested on diverse patient anatomies in simulations, TD-MPC2 outperformed the Soft Actor-Critic (SAC) algorithm with a 58% success rate (vs. 36%) and lower vessel contact forces (0.15 N). In vitro experiments using patient-specific phantoms showed comparable success rates (68% vs. 60%) but better path efficiency for TD-MPC2, though with longer procedure times. The results demonstrate the potential of world models for safer and more adaptable AI-driven endovascular interventions.
279openalex2026-04-03大月 智史, S. Otsuki, 八田 直樹, N. Hatta +7 more
This paper presents a hierarchical framework for ensuring safe vessel operations in ports using Control Barrier Functions (CBF), Model Predictive Control (MPC), and a Rapidly-exploring Random Tree (RRT)-like spatiotemporal path planning method. The approach integrates real-time collision avoidance and optimal trajectory planning to enhance navigation safety. The authors demonstrate the system's effectiveness through simulations and experiments in port environments. The proposed method aims to reduce risks and improve operational efficiency for autonomous or semi-autonomous vessels.
280openalex2026-04-02Jiyong Kwon, Ujin Jeon, Sooji Lee, Guang Lin
AIVV introduces a hybrid framework using Large Language Models (LLMs) to automate Verification and Validation (V&V) for autonomous systems. It addresses limitations of deep learning models in anomaly classification by deploying a role-specialized LLM council to collaboratively validate faults and assess system responses against natural-language requirements. The framework generates actionable V&V artifacts, such as gain-tuning proposals, and was tested successfully on a time-series simulator for Unmanned Underwater Vehicles (UUVs). AIVV aims to replace manual Human-in-the-Loop (HITL) processes, offering a scalable solution for system oversight.