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Unmanned Surface Vessels (USVs): Technology, Applications and Regulatory Landscapes
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Unmanned Surface Vessels (USVs): Technology, Applications and Regulatory Landscapes

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: 10 October 2026 | Viewed by 13128

Special Issue Editors

Prof. Dr. Antonio Carlos Fernandes

E-Mail Website
Guest Editor
Ocean Engineering Program, LOC/COPPE/UFRJ, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
Interests: ocean engineering; unmanned vehicles; maritime autonomy
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Joel Sena Sales Junior

E-Mail Website
Guest Editor
Department of Ocean Engineering, Federal University of Rio de Janeiro (COPPE/UFRJ), Rio de Janeiro, Brazil
Interests: hydrodynamics; dynamics of ocean systems; autonomous vehicles; artificial intelligence; mooring systems and risers; uncertainty analysis; model tests; renewable energy devices

Special Issue Information

Dear Colleagues,

Unmanned Surface Vessels (USVs) have received a great deal of attention in the last years. Since then, there has been extensive research on various aspects of unmanned vehicles. The purpose of the invited Special Issue is to publish the most exciting research concerning the above subjects and to provide a rapid turnaround time regarding reviewing and publishing, and to disseminate the articles freely for research, teaching, and reference purposes.

High-quality papers are encouraged for publication, directly related to various aspects of the USV technology, as mentioned below.

Topics

  • Unmanned Surface Vessels (autonomous and/or remote controlled)
  • Foundational technologies and design: hull, power and propulsion systems, and sensors
  • Guidance, Navigation, and Control (GNC) systems
  • Applications: scientific research, maritime safety, disaster response, and defense
  • Challenges and future research trends
  • Surveys and reviews

Prof. Dr. Antonio Carlos Fernandes
Prof. Dr. Joel Sena Sales Junior
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • unmanned surface vessel
  • autonomous surface vessel
  • autonomous vehicle
  • unmanned vehicle
  • maritime autonomy
  • maritime vehicles
  • autonomous navigation
  • intelligent control
  • unmanned system

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (7 papers)

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31 pages, 48945 KB  
Article
RF-LSTM-Based Motion State Prediction for Unmanned Surface Vehicles Under Variable Operating Conditions
by Pengpeng Wan, Liming Wang, Yexin Song, Bi He, Hua Ouyang and Xing Xu
J. Mar. Sci. Eng. 2026, 14(10), 885; https://doi.org/10.3390/jmse14100885 (registering DOI) - 10 May 2026
Viewed by 226
Abstract
As a core piece of equipment for marine monitoring, search and rescue missions, and other applications, the motion state prediction accuracy of Unmanned Surface Vehicles (USVs) directly determines mission reliability and safety. However, existing methods fail to fully consider the motion characteristic differences [...] Read more.
As a core piece of equipment for marine monitoring, search and rescue missions, and other applications, the motion state prediction accuracy of Unmanned Surface Vehicles (USVs) directly determines mission reliability and safety. However, existing methods fail to fully consider the motion characteristic differences in various vessel sizes and variable-speed navigation under complex sea conditions, and struggle to capture the spatiotemporal dynamic features of state variations. This paper proposes a hybrid prediction algorithm based on Random Forest-Long Short-Term Memory (RF-LSTM), which utilizes Random Forest for key feature selection while employing LSTM to excavate temporal correlations. An intelligent routing mechanism based on the dominant frequency energy ratio (Pd) is introduced to achieve adaptive prediction mode switching, enabling comprehensive characterization of state variations. Under the 20 kn high-speed condition of a 7.5 m USV, the proposed algorithm achieves a Circular RMSE for heading prediction that is 1.9 times lower than the Extended Kalman Filter (EKF) and 1.2 times lower than a standalone LSTM, with pitch and roll prediction RMSE reduced to 0.36° and 0.85°, respectively. On a 14.5 m-long USV at 23 kn, it maintains a heading prediction accuracy of 0.10°, verifying favorable scale generalization capability. Furthermore, the algorithm demonstrates strong robustness against Gaussian white noise and synthetic ocean noise. Experimental results indicate that RF-LSTM significantly outperforms traditional methods, effectively breaking through the application limitations of fixed-architecture models, substantially enhancing USV autonomy and adaptability in complex marine environments, and providing robust guarantees for mission reliability and safety. Full article
(This article belongs to the Special Issue Unmanned Surface Vessels (USVs): Technology, Applications and Regulatory Landscapes)
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17 pages, 1861 KB  
Article
Study and Feasibility of Underwater Acoustic Data Transmission
by Bessie A. Ribeiro, Fabio C. Xavier, Viviane R. Barroso, Viviane F. da Silva, Theodoro A. Netto and Caroline Ferraz
J. Mar. Sci. Eng. 2026, 14(7), 648; https://doi.org/10.3390/jmse14070648 - 31 Mar 2026
Viewed by 774
Abstract
The growing demand for offshore oil and gas production in deep waters has motivated the development of technologies to enable the continuous, reliable, and cost-effective monitoring of subsea equipment. Traditional inspection techniques rely on ROVs and AUVs, leading to delays between data acquisition [...] Read more.
The growing demand for offshore oil and gas production in deep waters has motivated the development of technologies to enable the continuous, reliable, and cost-effective monitoring of subsea equipment. Traditional inspection techniques rely on ROVs and AUVs, leading to delays between data acquisition and recovery and high operational costs. Underwater acoustic communication systems represent an attractive alternative for transmitting monitoring data to the surface in real time. This work evaluates the feasibility of implementing an underwater acoustic communication link for data transmission in deep-water environments, considering environmental conditions and acoustic channel characteristics. Using the BELLHOP ray-tracing model, simulations were performed to predict transmission loss, multipath effects, ambient noise, and the resulting signal-to-noise ratio (SNR) for different modem configurations and operating frequencies. The results demonstrate that the performance of the underwater link is strongly dependent on frequency, distance, and environmental variability. The study identifies optimal frequency–range relationships, quantifies the limitations imposed by transmission loss and ambient noise, and provides guidance for selecting acoustic modem parameters for real subsea monitoring applications. The SNR for three modem models operating at different frequencies illustrates the signal detection capability in the marine environment. The differences between modems A, B, and C are defined by their technical specifications and how they perform within the underwater acoustic channel of the Campos Basin. The data transmission capacity is supported by the data rates provided by the analyzed modems. The low frequencies of modem A (9.75 kHz) achieve the highest SNR, enabling long-range monitoring. At higher frequencies, modem C (78 kHz) allows short-distance communication. Modem B (35 kHz) offers a good balance between the data rate and power consumption, consuming only 1 W, making it highly viable for monitoring systems that rely on batteries and require long-term operation. The findings support the feasibility of integrating underwater acoustic communication into subsea monitoring architectures, enabling a more efficient oversight of deep-water production systems. The analysis concludes that project viability depends on selecting a system where the SNR and range meet the specific monitoring requirements. Full article
(This article belongs to the Special Issue Unmanned Surface Vessels (USVs): Technology, Applications and Regulatory Landscapes)
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27 pages, 8178 KB  
Article
A Hierarchical, Modular Interface and Verification Architecture for Mission Planning in Swarm Unmanned Surface Vehicles: Simulation and Sea-Trial Validation
by Hee-Mun Park, Jin-Hyeon Sung, Hong-Sun Park, Yeong-Hyun Lim, Joono Sur and Kyung-Min Seo
J. Mar. Sci. Eng. 2026, 14(3), 302; https://doi.org/10.3390/jmse14030302 - 4 Feb 2026
Viewed by 856
Abstract
Swarm Unmanned Surface Vehicles (SUSV) must sustain real-time coordination as fleet scale and formation change. We propose hierarchical and modular architecture that decouples mission-planning algorithms from interface evolution, composed of an Interface Adapter System (IAS), a Mission Execution System (MES), and an Interoperation [...] Read more.
Swarm Unmanned Surface Vehicles (SUSV) must sustain real-time coordination as fleet scale and formation change. We propose hierarchical and modular architecture that decouples mission-planning algorithms from interface evolution, composed of an Interface Adapter System (IAS), a Mission Execution System (MES), and an Interoperation Integration Verification System (IIVS). The IAS standardizes and integrates data from diverse sensors and subsystems through modular adapters, facilitating flexible subsystem integration. The MES employs a discrete-event system specification (DEVS)-based modeling approach, providing independent and efficient mission execution capability without necessitating interface modifications. The IIVS utilizes LabVIEW-based analytical methods to verify and validate subsystem interoperability continuously, enabling rapid and reliable scaling. The architecture was implemented in an operational SUSV program and evaluated through simulation experiments and sea trials. During scale-up from 10 to 20 USVs, mission-cycle deadlines (≤250 ms) were met in 99% of cases, while integration lead time for scale-up decreased by about 80%. Message-level tests confirmed robust interoperation under increased load, and algorithm-level tests showed stable plan re-computation under dynamic tasking. These results indicate improved interoperability, scalability, and reliability, offering a practical blueprint for mission planning in maritime swarms. Full article
(This article belongs to the Special Issue Unmanned Surface Vessels (USVs): Technology, Applications and Regulatory Landscapes)
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25 pages, 27323 KB  
Article
Toward Safe Autonomy at Sea: Implementation and Field Validation of COLREGs-Compliant Collision-Avoidance for Unmanned Surface Vessels
by Douglas Silva de Lima, Gustavo Alencar Bisinotto and Eduardo Aoun Tannuri
J. Mar. Sci. Eng. 2025, 13(12), 2366; https://doi.org/10.3390/jmse13122366 - 12 Dec 2025
Cited by 1 | Viewed by 1247
Abstract
The growing adoption of Unmanned Surface Vessels (USVs) in commercial and defense domains raises challenges for safe navigation and strict adherence to the International Regulations for Preventing Collisions at Sea (COLREGs). This paper presents the implementation and field validation of three collision-avoidance approaches [...] Read more.
The growing adoption of Unmanned Surface Vessels (USVs) in commercial and defense domains raises challenges for safe navigation and strict adherence to the International Regulations for Preventing Collisions at Sea (COLREGs). This paper presents the implementation and field validation of three collision-avoidance approaches on a real USV: (i) behavior-based, (ii) a modified Velocity Obstacles (VO) algorithm, and (iii) a modified A* path-planning algorithm. Field trials in Guanabara Bay (Brazil) show that the behavior-based algorithm achieved the best balance between safety and efficiency, maintaining a safe mean Closest Point of Approach (30.0 m) while minimizing operational penalties: shortest total distance (179.4 m average), lowest mission completion time (174.7 s average), and smallest trajectory deviation (27.2% average increase). The VO algorithm operated with reduced safety margins (13.0 m average CPA) at the expense of larger detours (37.6% average distance increase), while the modified A* maintained equivalent safety (30.0 m average CPA) but produced the largest deviations (46.5% average increase). The trade-off analysis reveals that algorithm selection depends on operational priorities between safety margins and route efficiency. Full article
(This article belongs to the Special Issue Unmanned Surface Vessels (USVs): Technology, Applications and Regulatory Landscapes)
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21 pages, 31599 KB  
Article
Deformable USV and Lightweight ROV Collaboration for Underwater Object Detection in Complex Harbor Environments: From Acoustic Survey to Optical Verification
by Yonghang Li, Mingming Wen, Peng Wan, Zelin Mu, Dongqiang Wu, Jiale Chen, Haoyi Zhou, Shi Zhang and Huiqiang Yao
J. Mar. Sci. Eng. 2025, 13(10), 1862; https://doi.org/10.3390/jmse13101862 - 26 Sep 2025
Cited by 1 | Viewed by 4841
Abstract
As crucial transportation hubs and economic nodes, the underwater security and infrastructure maintenance of harbors are of paramount importance. Harbors are characterized by high vessel traffic and complex underwater environments, where traditional underwater inspection methods, such as diver operations, face challenges of low [...] Read more.
As crucial transportation hubs and economic nodes, the underwater security and infrastructure maintenance of harbors are of paramount importance. Harbors are characterized by high vessel traffic and complex underwater environments, where traditional underwater inspection methods, such as diver operations, face challenges of low efficiency, high risk, and limited operational range. This paper introduces a collaborative survey and disposal system that integrates a deformable unmanned surface vehicle (USV) with a lightweight remotely operated vehicle (ROV). The USV is equipped with a side-scan sonar (SSS) and a multibeam echo sounder (MBES), enabling rapid, large-area searches and seabed topographic mapping. The ROV, equipped with an optical camera system, forward-looking sonar (FLS), and a manipulator, is tasked with conducting close-range, detailed observations to confirm and dispose of abnormal objects identified by the USV. Field trials were conducted at an island harbor in the South China Sea, where simulated underwater objects, including an iron drum, a plastic drum, and a rubber tire, were deployed. The results demonstrate that the USV-ROV collaborative system effectively meets the demands for underwater environmental measurement, object localization, identification, and disposal in complex harbor environments. The USV acquired high-resolution (0.5 m × 0.5 m) three-dimensional topographic data of the harbor, effectively revealing its topographical features. The SSS accurately localized and preliminarily identified all deployed simulated objects, revealing their acoustic characteristics. Repeated surveys revealed a maximum positioning deviation of 2.2 m. The lightweight ROV confirmed the status and location of the simulated objects using an optical camera and an underwater positioning system, with a maximum deviation of 3.2 m when compared to the SSS locations. The study highlights the limitations of using either vehicle alone. The USV survey could not precisely confirm the attributes of the objects, whereas a full-area search of 0.36 km2 by the ROV alone would take approximately 20 h. In contrast, the USV-ROV collaborative model reduced the total time to detect all objects to 9 h, improving efficiency by 55%. This research offers an efficient, reliable, and economical practical solution for applications such as underwater security, topographic mapping, infrastructure inspection, and channel dredging in harbor environments. Full article
(This article belongs to the Special Issue Unmanned Surface Vessels (USVs): Technology, Applications and Regulatory Landscapes)
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26 pages, 3429 KB  
Article
I-VoxICP: A Fast Point Cloud Registration Method for Unmanned Surface Vessels
by Qianfeng Jing, Mingwang Bai, Yong Yin and Dongdong Guo
J. Mar. Sci. Eng. 2025, 13(10), 1854; https://doi.org/10.3390/jmse13101854 - 25 Sep 2025
Cited by 2 | Viewed by 1242
Abstract
The accurate positioning and state estimation of surface vessels are prerequisites to autonomous navigation. Recently, the rapid development of 3D LiDARs has promoted the autonomy of both land and aerial vehicles, which has attracted the interest of researchers in the maritime community. However, [...] Read more.
The accurate positioning and state estimation of surface vessels are prerequisites to autonomous navigation. Recently, the rapid development of 3D LiDARs has promoted the autonomy of both land and aerial vehicles, which has attracted the interest of researchers in the maritime community. However, in traditional maritime surface multi-scenario applications, LiDAR scan matching has low point cloud scanning and matching efficiency and insufficient positional accuracy when dealing with large-scale point clouds, so it has difficulty meeting the real-time demand of low-computing-power platforms. In this paper, we use ICP-SVD for point cloud alignment in the Stanford dataset and outdoor dock scenarios and propose an optimization scheme (iVox + ICP-SVD) that incorporates the voxel structure iVox. Experiments show that the average search time of iVox is 72.23% and 96.8% higher than that of ikd-tree and kd-tree, respectively. Executed on an NVIDIA Jetson Nano (four ARM Cortex-A57 cores @ 1.43 GHz) the algorithm processes 18 k downsampled points in 56 ms on average and 65 ms in the worst case—i.e., ≤15 Hz—so every scan is completed before the next 10–20 Hz LiDAR sweep arrives. During a 73 min continuous harbor trial the CPU temperature stabilized at 68 °C without thermal throttling, confirming that the reported latency is a sustainable, field-proven upper bound rather than a laboratory best case. This dramatically improves the retrieval efficiency while effectively maintaining the matching accuracy. As a result, the overall alignment process is significantly accelerated, providing an efficient and reliable solution for real-time point cloud processing. Full article
(This article belongs to the Special Issue Unmanned Surface Vessels (USVs): Technology, Applications and Regulatory Landscapes)
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22 pages, 15811 KB  
Technical Note
A Low-Cost, Open-Source, Multi-Purpose Autonomous Surface Vehicle
by Thomaz Augusto Kras Benatti, Emerson Martins de Andrade, Maicon Rodrigo Correa, Felipe da Silva Lopes, João Paulo Machado dos Santos Bernardino, Joel Sena Sales, Jr. and Antonio Carlos Fernandes
J. Mar. Sci. Eng. 2025, 13(12), 2380; https://doi.org/10.3390/jmse13122380 - 16 Dec 2025
Cited by 1 | Viewed by 2298
Abstract
Autonomous surface vehicles (ASVs) have played a crucial role in various areas, including oceanographic research, environmental monitoring, and asset inspection. However, the high cost and proprietary nature of many platforms limit accessibility. Thus, this work introduces a low-cost, fully open-source ASV platform designed [...] Read more.
Autonomous surface vehicles (ASVs) have played a crucial role in various areas, including oceanographic research, environmental monitoring, and asset inspection. However, the high cost and proprietary nature of many platforms limit accessibility. Thus, this work introduces a low-cost, fully open-source ASV platform designed to support a wide range of applications, from academic research to community-driven monitoring projects, bridging the existing gap between low-cost prototyping and naval architecture-based ASV development. Featuring a modular 2 m hull design, the vehicle integrates off-the-shelf components and open-source software to ensure affordability, flexibility, and ease of replication. Field tests were conducted on Ilha do Fundão (Fundão Island), located within the campus of the Federal University of Rio de Janeiro (UFRJ), Brazil. All design files and code are released on GitHub (version 1.0.0) to encourage adoption and collaborative improvement. Full article
(This article belongs to the Special Issue Unmanned Surface Vessels (USVs): Technology, Applications and Regulatory Landscapes)
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