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: 20 April 2026 | Viewed by 5066

Special Issue Editors


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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

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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

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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 monthly 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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Published Papers (2 papers)

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Research

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
Viewed by 3688
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
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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 1 | Viewed by 617
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
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