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The Control and Navigation of Autonomous Surface Vehicles
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The Control and Navigation of Autonomous Surface Vehicles

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: 30 April 2025 | Viewed by 1030

Special Issue Editors

Prof. Dr. Defeng Wu

E-Mail Website
Guest Editor
School of Marine Engineering, Jimei University, Xiamen, China
Interests: systems and control theory; machining learning; reinforcement learning; computational intelligence, and its applications in marine engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Zhiming Yuan

E-Mail Website
Guest Editor
Department of Naval Architecture, Ocean and Marine Engineering, University of Strathclyde, Glasgow, UK
Interests: offshore integrated renewable energy system; dynamics of offshore structures; multibody hydrodynamic interaction and wave interference; ship-bottom; ship-bank; ship-lock; ship-ship interactions
Special Issues, Collections and Topics in MDPI journals
Dr. Haitong Xu

E-Mail Website
Guest Editor
Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
Interests: maneuvering modeling; guidance and control systems; collision avoidance; data acquisition (DAQ) and developing prototypes of autonomous surface ships
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the rapid advancement of modern control and navigation technologies, autonomous surface vehicles (USVs) are evolving into more integrated, interoperable, efficient and adaptive systems, suitable for executing a wide range of complex ocean tasks. Recently, researchers have increasingly used intelligent control and advanced navigation technologies, including autonomous perception and positioning, real-time decision-making, mission planning and collaborative formation, to deal with the real-world challenges characterized by high uncertainty, variability and unpredictability. The goal of this Special Issue is to enhance the reliability, robustness and accuracy of control and navigation, endowing USVs with autonomous perception, adaptive intelligent decision-making and control capabilities and further facilitating their applications. We invite researchers from both academia and industry to submit original articles in the following areas: 

  • Advanced sensing technology;
  • Multi-source data fusion;
  • Autonomous positioning and navigation;
  • Obstacle avoidance and path planning in dynamic ocean environments;
  • Application of artificial intelligence in USVs;
  • Intelligent decision-making framework design in complex ocean environments;
  • Adaptive methods and high-precision control in USVs;
  • Self-organizing network technology in USVs;
  • Heterogeneous USV collaborative control;
  • Simulation and modeling of USVs.

Prof. Dr. Defeng Wu
Dr. Zhiming Yuan
Dr. Haitong Xu
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 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • autonomous surface vehicles (USVs)
  • autonomous positioning and navigation
  • intelligent decision-making
  • adaptive control
  • collaborative control
  • sensing technology
  • artificial intelligence

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

Published Papers (3 papers)

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25 pages, 20538 KiB  
Article
Leader-Following-Based Optimal Fault-Tolerant Consensus Control for Air–Marine–Submarine Heterogeneous Systems
by Yandong Li, Longqi Li, Ling Zhu, Zehua Zhang and Yuan Guo
J. Mar. Sci. Eng. 2025, 13(5), 878; https://doi.org/10.3390/jmse13050878 (registering DOI) - 28 Apr 2025
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Abstract
This paper mainly investigates the fault-tolerant consensus problem in heterogeneous multi-agent systems. Firstly, a control model of a leader–follower heterogeneous multi-agent system (HMAS) composed of multiple unmanned aerial vehicles (UAVs), multiple unmanned surface vehicles (USVs), and multiple unmanned underwater vehicles (UUVs) is established. [...] Read more.
This paper mainly investigates the fault-tolerant consensus problem in heterogeneous multi-agent systems. Firstly, a control model of a leader–follower heterogeneous multi-agent system (HMAS) composed of multiple unmanned aerial vehicles (UAVs), multiple unmanned surface vehicles (USVs), and multiple unmanned underwater vehicles (UUVs) is established. Then, for the fault-tolerant control (FTC) consensus problem of heterogeneous systems under partial actuator failures and interruption failures, an optimal FTC protocol for heterogeneous multi-agent systems based on the control allocation algorithm is designed. The derived optimal FTC protocol is applied to the heterogeneous system. The asymptotic stability of the protocol is proved by the Lyapunov stability theory. Finally, the effectiveness of the control strategy is verified through simulation tests. Full article
(This article belongs to the Special Issue The Control and Navigation of Autonomous Surface Vehicles)
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23 pages, 10158 KiB  
Article
Navigation and Obstacle Avoidance for USV in Autonomous Buoy Inspection: A Deep Reinforcement Learning Approach
by Jianhui Wang, Zhiqiang Lu, Xunjie Hong, Zeye Wu and Weihua Li
J. Mar. Sci. Eng. 2025, 13(5), 843; https://doi.org/10.3390/jmse13050843 - 24 Apr 2025
Viewed by 193
Abstract
To address the challenges of manual buoy inspection, this study enhances a previously proposed Unmanned Surface Vehicle (USV) inspection system by improving its navigation and obstacle avoidance capabilities using Proximal Policy Optimization (PPO). For improved usability, the entire system adopts a fully end-to-end [...] Read more.
To address the challenges of manual buoy inspection, this study enhances a previously proposed Unmanned Surface Vehicle (USV) inspection system by improving its navigation and obstacle avoidance capabilities using Proximal Policy Optimization (PPO). For improved usability, the entire system adopts a fully end-to-end design, with an angular deviation weighting mechanism for stable circular navigation, a novel image-based radar encoding technique for obstacle perception and a decoupled navigation and obstacle avoidance architecture that splits the complex task into three independently trained modules. Experiments validate that both navigation modules exhibit robustness and generalization capabilities, while the obstacle avoidance module partially achieves International Regulations for Preventing Collisions at Sea (COLREGs)-compliant maneuvers. Further tests in continuous multi-buoy inspection tasks confirm the architecture’s effectiveness in integrating these modules to complete the full task. Full article
(This article belongs to the Special Issue The Control and Navigation of Autonomous Surface Vehicles)
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22 pages, 6362 KiB  
Article
Target-Defense Games with One or Two Unmanned Surface Vehicles Defending an Island: A Geometric Analytical Approach
by Keyang Wang, Yintao Wang and Qi Sun
J. Mar. Sci. Eng. 2025, 13(2), 365; https://doi.org/10.3390/jmse13020365 - 16 Feb 2025
Viewed by 711
Abstract
This paper considers a target-defense game in an open area with one or two defenders as well as an intruder. The intruder endeavors to reach the boundary of the island, while the defenders strive to prevent that by capturing the intruder through contact. [...] Read more.
This paper considers a target-defense game in an open area with one or two defenders as well as an intruder. The intruder endeavors to reach the boundary of the island, while the defenders strive to prevent that by capturing the intruder through contact. Islands, as closed areas, restrict the free movement of the defenders, since the defenders—represented by USVs—cannot traverse the target area directly. First, we are concerned with the barrier, which is the boundary of the winning zones, taking into account the impact of the target. For the initial states lying in the defenders’ winning zone, there exists a strategy for the defenders to intercept the intruder regardless of the intruder’s best effort, while for the initial states lying in the intruder’s winning zone, the intruder can always invade successfully. We propose a geometric method to construct the barrier analytically for two kinds of speed ratios. Then, by taking index functions into consideration, we present optimal strategies for the players after constructing the dominance regions when their initial states lie in different winning zones. Simulation results verify the effectiveness of the proposed method. This study can be extended to scenarios involving multiple defenders. Full article
(This article belongs to the Special Issue The Control and Navigation of Autonomous Surface Vehicles)
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