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Design and Application of Underwater Vehicles
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Design and Application of Underwater 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: 10 February 2026 | Viewed by 3207

Special Issue Editor

Prof. Dr. Zhiguang Feng

E-Mail Website
Guest Editor
College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150001, China
Interests: intelligent control; underwater vehicles; neural network

Special Issue Information

Dear Colleagues,

Underwater vehicles are part of the core technical equipment used for exploring and developing marine resources. Their designs and applications have irreplaceable strategic value in deep sea exploration, environmental monitoring, seabed resource surveying, and military security. With the continuous growth in the global demand for marine resources, underwater vehicles can not only perform high-precision seabed topography mapping and biodiversity surveys and other scientific tasks, but also be applied in the maintenance of seabed infrastructure (such as oil and gas pipelines and optical cable inspection) and marine disaster early warning scenarios, as well as other practical scenarios. Facing complex and changeable marine environments (such as high pressure, strong turbulence, and extreme temperature gradients), the design of underwater vehicles needs to balance energy efficiency and system reliability and use intelligent control algorithms (such as model predictive control and adaptive path planning) to deal with dynamic disturbances, ensuring the stability and safety of task execution. In addition, the autonomous operation ability of underwater vehicles under extreme conditions provides key technical support for advancing marine scientific research and environmental protection.

The research and development of underwater vehicles reflects the achievements of multi-disciplinary integration, covering mechanical structure optimization, intelligent perception system integration, and energy management strategies. Their design needs to address core issues such as multi-degree-of-freedom motion control, improvements in long-endurance capabilities, and the optimization of environmental adaptability, such as by using lightweight materials and modular architectures to reduce energy consumption and also by integrating data-driven real-time decision-making systems to enhance their obstacle avoidance and trajectory-tracking capabilities. High-precision numerical modeling and simulation technologies have further improved their operational accuracy in non-ideal environments, such as complex ocean currents and sensor noise. The combination of distributed sensor networks and artificial intelligence algorithms has also promoted the realization of fully autonomous and intelligent underwater operations. These technological innovations not only accelerate the progress of marine science and engineering, but also lay a solid foundation for future deep sea resource development, ecological protection, and global ocean governance.

Prof. Dr. Zhiguang Feng
Guest Editor

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

  • underwater vehicles
  • artificial intelligence
  • autonomous underwater vehicles
  • deep sea exploration

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Published Papers (6 papers)

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Research

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26 pages, 101982 KB  
Article
Hydrodynamic Optimization and Motion Stability Enhancement of Underwater Glider Combining CFD and MOPSO
by Tian Zhang, Jiaming Wu, Xianyuan Yang and Xiaodong Chen
J. Mar. Sci. Eng. 2025, 13(9), 1749; https://doi.org/10.3390/jmse13091749 - 10 Sep 2025
Viewed by 215
Abstract
This study investigated the motion stability of underwater gliders and optimized their shape to enhance hydrodynamic performance. Given the critical role of stability in underwater operations, a multi-objective optimization framework was developed, focusing on the geometric configuration of hydrofoils. Computational fluid dynamics (CFD) [...] Read more.
This study investigated the motion stability of underwater gliders and optimized their shape to enhance hydrodynamic performance. Given the critical role of stability in underwater operations, a multi-objective optimization framework was developed, focusing on the geometric configuration of hydrofoils. Computational fluid dynamics (CFD) simulations were employed, with stability assessed based on hydrodynamic moments in roll and pitch motions. A surrogate model was constructed using Kriging interpolation, leveraging Latin hypercube sampling (LHS) to generate 60 design points. Sensitivity analysis identified key shape parameters influencing stability, guiding a multi-objective particle swarm optimization (MOPSO) algorithm to explore optimal design configurations. Improvements of up to 68.91% in roll stability and 51.63% in pitch stability are achieved compared to the original model, which demonstrates the effectiveness of the proposed optimization approach. The findings provide valuable insights into the hydrodynamic design of underwater gliders, facilitating enhanced maneuverability and stability in complex marine environments. Full article
(This article belongs to the Special Issue Design and Application of Underwater Vehicles)
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22 pages, 10200 KB  
Article
Research on Self-Noise Processing of Unmanned Surface Vehicles via DD-YOLO Recognition and Optimized Time-Frequency Denoising
by Zhichao Lv, Gang Wang, Huming Li, Xiangyu Wang, Fei Yu, Guoli Song and Qing Lan
J. Mar. Sci. Eng. 2025, 13(9), 1710; https://doi.org/10.3390/jmse13091710 - 4 Sep 2025
Viewed by 363
Abstract
This research provides a new systematic solution to the essential issue of self-noise interference in underwater acoustic sensing signals induced by unmanned surface vehicles (USVs) operating at sea. The self-noise pertains to the near-field interference noise generated by the growing diversity and volume [...] Read more.
This research provides a new systematic solution to the essential issue of self-noise interference in underwater acoustic sensing signals induced by unmanned surface vehicles (USVs) operating at sea. The self-noise pertains to the near-field interference noise generated by the growing diversity and volume of acoustic equipment utilized by USVs. The generating mechanism of self-noise is clarified, and a self-noise propagation model is developed to examine its three-dimensional coupling properties within spatiotemporal fluctuation environments in the time-frequency-space domain. On this premise, the YOLOv11 object identification framework is innovatively applied to the delay-Doppler (DD) feature maps of self-noise, thereby overcoming the constraints of traditional time-frequency spectral approaches in recognizing noise with delay spread and overlapping characteristics. A comprehensive comparison with traditional models like YOLOv8 and SSD reveals that the suggested delay-Doppler YOLO (DD-YOLO) algorithm attains an average accuracy of 87.0% in noise source identification. An enhanced denoising method, termed optimized time-frequency regularized overlapping group shrinkage (OTFROGS), is introduced, using structural sparsity alongside non-convex regularization techniques. Comparative experiments with traditional denoising methods, such as the normalized least mean square (NLMS) algorithm, wavelet threshold denoising (WTD), and the original time-frequency regularized overlapping group shrinkage (TFROGS), reveal that OTFROGS outperforms them in mitigating USV self-noise. This study offers a dependable technological approach for optimizing the performance of USV acoustic systems and proposes a theoretical framework and methodology applicable to different underwater acoustic sensing contexts. Full article
(This article belongs to the Special Issue Design and Application of Underwater Vehicles)
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23 pages, 12274 KB  
Article
Predefined-Time Formation Tracking Control for Underactuated AUVs with Input Saturation and Output Constraints
by Sibo Yao, Yiqi Wang and Zhiguang Feng
J. Mar. Sci. Eng. 2025, 13(9), 1607; https://doi.org/10.3390/jmse13091607 - 22 Aug 2025
Viewed by 337
Abstract
In this work, a predefined-time formation output constraint control method is proposed for underactuated AUVs with input saturation. First, a coordinate transformation method is utilized to convert the underactuated AUV system into a fully actuated system form. A universal time-varying asymmetric barrier function [...] Read more.
In this work, a predefined-time formation output constraint control method is proposed for underactuated AUVs with input saturation. First, a coordinate transformation method is utilized to convert the underactuated AUV system into a fully actuated system form. A universal time-varying asymmetric barrier function is constructed to convert the system to an unconstrained form and construct the formation tracking error. Then, a predefined-time formation output constraint control law is designed based on the active disturbance rejection control framework and predefined-time control method, which can achieve the control objective without relying on the precise mathematical model of the system. In addition, to address the input saturation issue, a novel predefined-time auxiliary dynamic system (ADS) is proposed. The proposed method with ADS can ensure that the multi-AUV system with input saturation can complete the formation output constraint tracking control task within a predefined time. Finally, a simulation is designed to verify the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Design and Application of Underwater Vehicles)
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20 pages, 2749 KB  
Article
ROVs Utilized in Communication and Remote Control Integration Technologies for Smart Ocean Aquaculture Monitoring Systems
by Yen-Hsiang Liao, Chao-Feng Shih, Jia-Jhen Wu, Yu-Xiang Wu, Chun-Hsiang Yang and Chung-Cheng Chang
J. Mar. Sci. Eng. 2025, 13(7), 1225; https://doi.org/10.3390/jmse13071225 - 25 Jun 2025
Viewed by 997
Abstract
This study presents a new intelligent aquatic farming surveillance system that tackles real-time monitoring challenges in the industry. The main technical break-throughs of this system are evident in four key aspects: First, it achieves the smooth integration of remotely operated vehicles (ROVs), sensors, [...] Read more.
This study presents a new intelligent aquatic farming surveillance system that tackles real-time monitoring challenges in the industry. The main technical break-throughs of this system are evident in four key aspects: First, it achieves the smooth integration of remotely operated vehicles (ROVs), sensors, and real-time data transmission. Second, it uses a mobile communication architecture with buoy relay stations for distributed edge computing. This design supports future upgrades to Beyond 5G and satellite networks for deep-sea applications. Third, it features a multi-terminal control system that supports computers, smartphones, smartwatches, and centralized hubs, effectively enabling monitoring anytime, anywhere. Fourth, it incorporates a cost-effective modular design, utilizing commercial hardware and innovative system integration solutions, making it particularly suitable for farms with limited resources. The data indicates that the system’s 4G connection is both stable and reliable, demonstrating excellent performance in terms of data transmission success rates, control command response delays, and endurance. It has successfully processed 324,800 data transmission events, thoroughly validating its reliability in real-world production environments. This system integrates advanced technologies such as the Internet of Things, mobile communications, and multi-access control, which not only significantly enhance the precision oversight capabilities of marine farming but also feature a modular design that allows for future expansion into satellite communications. Notably, the system reduces operating costs while simultaneously improving aquaculture efficiency, offering a practical and intelligent solution for small farmers in resource-limited areas. Full article
(This article belongs to the Special Issue Design and Application of Underwater Vehicles)
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23 pages, 2564 KB  
Article
Hierarchical Adaptive Fixed-Time Formation Control for Multiple Underactuated Autonomous Underwater Vehicles Under Uncertain Disturbances and Input Saturation
by Jiacheng Chang, Lanyong Zhang, Yifan Tan, Xue Fu and Hongjun Yu
J. Mar. Sci. Eng. 2025, 13(6), 1146; https://doi.org/10.3390/jmse13061146 - 9 Jun 2025
Viewed by 697
Abstract
Recent advances in multiple autonomous underwater vehicles (AUVs) have highlighted formation control as a critical challenge for underwater collaborative operations. To address the inherent coupling between formation coordination and individual control in conventional approaches, this paper proposes a novel hierarchical framework of adaptive [...] Read more.
Recent advances in multiple autonomous underwater vehicles (AUVs) have highlighted formation control as a critical challenge for underwater collaborative operations. To address the inherent coupling between formation coordination and individual control in conventional approaches, this paper proposes a novel hierarchical framework of adaptive fixed-time formation control for multiple underactuated AUVs. This framework decouples AUVs’ formation requirements and individual control challenges into two distinct layers: the Collision-free Formation Trajectories Generation (CFTG) Layer and the Adaptive Trajectories Tracking (ATT) Layer. In the CFTG Layer, a consensus-based controller is developed to generate the desired trajectories for the AUVs to meet the requirements of complex formation tasks. And an improved artificial potential field method is proposed to ensure AUVs can reach the target point when the target is close to obstacles. In the ATT Layer, an auxiliary compensation system is designed to address the issue of input saturation. Furthermore, the adaptive fixed-time controllers are proposed to handle the uncertain parameters in the model, enabling underactuated AUVs to track the desired trajectory precisely. Both layers guarantee fixed-time convergence to increase the convergence speed. Simulations are conducted to demonstrate the effectiveness and better performance of the proposed method. Full article
(This article belongs to the Special Issue Design and Application of Underwater Vehicles)
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Review

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26 pages, 4820 KB  
Review
Variable-Stiffness Underwater Robotic Systems: A Review
by Peiwen Lu, Busheng Dong, Xiang Gao, Fujian Zhang, Yunyun Song, Zhen Liu and Zhongqiang Zhang
J. Mar. Sci. Eng. 2025, 13(9), 1805; https://doi.org/10.3390/jmse13091805 - 18 Sep 2025
Viewed by 118
Abstract
Oceans, which cover more than 70% of Earth’s surface, are home to vast biological and mineral resources. Deep-sea exploration encounters significant challenges due to harsh environmental factors, including low temperatures, high pressure, and complex hydrodynamic forces. These constraints have led to the widespread [...] Read more.
Oceans, which cover more than 70% of Earth’s surface, are home to vast biological and mineral resources. Deep-sea exploration encounters significant challenges due to harsh environmental factors, including low temperatures, high pressure, and complex hydrodynamic forces. These constraints have led to the widespread use of underwater robots as essential tools for deep-sea resource exploration and exploitation. Conventional underwater robots, whether rigid with fixed stiffness or fully flexible, fail to achieve the propulsion efficiency observed in biological fish. To overcome this limitation, researchers have developed adjustable stiffness mechanisms for robotic fish designs. This innovation strikes a balance between structural rigidity for stability and flexible adaptability to dynamic environments. By dynamically adjusting localized stiffness, these bio-inspired robots can alter their mechanical properties in real time. This capability improves propulsion efficiency, energy utilization, and resilience to external disturbances during operation. This paper begins by reviewing the evolution of underwater robots, from fixed-stiffness systems to adjustable-stiffness designs. Next, existing methods for stiffness adjustment are categorized into two approaches: offline component replacement and online real-time adaptation. The principles, implementation strategies, and comparative advantages of each approach are then analyzed. Finally, we identify the current challenges in adjustable-stiffness underwater robotics and propose future directions, such as advancements in intelligent sensing, autonomous stiffness adaptation, and enhanced performance in extreme environments. Full article
(This article belongs to the Special Issue Design and Application of Underwater Vehicles)
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