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Underwater Navigation, Guidance and Control Technology in Ocean Engineering
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Underwater Navigation, Guidance and Control Technology in Ocean Engineering

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Navigation and Positioning".

Deadline for manuscript submissions: closed (30 May 2025) | Viewed by 3598

Special Issue Editor

Prof. Dr. Daming Zhou

E-Mail Website
Guest Editor
School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China
Interests: prognostics and health management in renewable energy system; energy management strategy; fuel cell system modeling, diagnostic and prognostic
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The ocean covers two thirds of the earth's surface area and contains rich minerals, oil, and gas resources. Therefore, research on ocean engineering technology is of great significance to the development of humanity. Various kinds of state-to-art engineering techniques are involved in exploring the ocean, such as underwater target electromagnetic and acoustic detection, classification, location, and tracking approaches, advanced signal processing techniques for underwater platforms such as buoys or unmanned underwater vehicles (UUVs) and surface vessels, UUV collaboration and path planning, underwater vehicle formation, cluster control, collaborative control, communication, positioning, navigation, sensing, path planning and energy optimization technologies, underwater signal communication and networking, advanced navigation, and guidance and control applications for underwater or surface platforms.

After decades of development, various interdisciplinary combined technologies have been developed in ocean engineering. However, these technologies still face challenges due to the complex and harsh marine environment. The aim of this Special Issue is to gather the latest underwater navigation, guidance and control technologies in ocean engineering.

Potential topics include, but are not limited to, the following:

  • Underwater electromagnetic detection technology;
  • Underwater navigation, guidance and control technology;
  • Underwater target detection, classification, localization, and tracking;
  • UUVs formation and coordination control;
  • UUVs path planning technology;
  • Underwater acoustic propagation and ocean ambient noise;
  • Underwater signal communication and processing;
  • Application of artificial intelligence in ocean engineering;
  • Ocean acoustic parameters acquisition technology;
  • New technologies in ocean equipment;
  • Underwater technologies exhibition of embedded systems.

Prof. Dr. Daming Zhou
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. Sensors 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

  • underwater navigation, guidance and control
  • underwater target electromagnetic and acoustic detection
  • UUV collaboration and path planning
  • ocean engineering

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

Published Papers (2 papers)

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Research

40 pages, 7941 KB  
Article
Synergistic Hierarchical AI Framework for USV Navigation: Closing the Loop Between Swin-Transformer Perception, T-ASTAR Planning, and Energy-Aware TD3 Control
by Haonan Ye, Hongjun Tian, Qingyun Wu, Yihong Xue, Jiayu Xiao, Guijie Liu and Yang Xiong
Sensors 2025, 25(15), 4699; https://doi.org/10.3390/s25154699 - 30 Jul 2025
Viewed by 688
Abstract
Autonomous Unmanned Surface Vehicle (USV) operations in complex ocean engineering scenarios necessitate robust navigation, guidance, and control technologies. These systems require reliable sensor-based object detection and efficient, safe, and energy-aware path planning. To address these multifaceted challenges, this paper proposes a novel synergistic [...] Read more.
Autonomous Unmanned Surface Vehicle (USV) operations in complex ocean engineering scenarios necessitate robust navigation, guidance, and control technologies. These systems require reliable sensor-based object detection and efficient, safe, and energy-aware path planning. To address these multifaceted challenges, this paper proposes a novel synergistic AI framework. The framework integrates (1) a novel adaptation of the Swin-Transformer to generate a dense, semantic risk map from raw visual data, enabling the system to interpret ambiguous marine conditions like sun glare and choppy water, enabling real-time environmental understanding crucial for guidance; (2) a Transformer-enhanced A-star (T-ASTAR) algorithm with spatio-temporal attentional guidance to generate globally near-optimal and energy-aware static paths; (3) a domain-adapted TD3 agent featuring a novel energy-aware reward function that optimizes for USV hydrodynamic constraints, making it suitable for long-endurance missions tailored for USVs to perform dynamic local path optimization and real-time obstacle avoidance, forming a key control element; and (4) CUDA acceleration to meet the computational demands of real-time ocean engineering applications. Simulations and real-world data verify the framework’s superiority over benchmarks like A* and RRT, achieving 30% shorter routes, 70% fewer turns, 64.7% fewer dynamic collisions, and a 215-fold speed improvement in map generation via CUDA acceleration. This research underscores the importance of integrating powerful AI components within a hierarchical synergy, encompassing AI-based perception, hierarchical decision planning for guidance, and multi-stage optimal search algorithms for control. The proposed solution significantly advances USV autonomy, addressing critical ocean engineering challenges such as navigation in dynamic environments, object avoidance, and energy-constrained operations for unmanned maritime systems. Full article
(This article belongs to the Special Issue Underwater Navigation, Guidance and Control Technology in Ocean Engineering)
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23 pages, 10647 KB  
Article
Research on Multiple-AUVs Collaborative Detection and Surrounding Attack Simulation
by Zhiwen Wen, Zhong Wang, Daming Zhou, Dezhou Qin, Yichen Jiang, Junchang Liu and Huachao Dong
Sensors 2024, 24(2), 437; https://doi.org/10.3390/s24020437 - 10 Jan 2024
Cited by 3 | Viewed by 1868
Abstract
Due to limitations in operational scope and efficiency, a single Autonomous Underwater Vehicle (AUV) falls short of meeting the demands of the contemporary marine working environment. Consequently, there is a growing interest in the coordination of multiple AUVs. To address the requirements of [...] Read more.
Due to limitations in operational scope and efficiency, a single Autonomous Underwater Vehicle (AUV) falls short of meeting the demands of the contemporary marine working environment. Consequently, there is a growing interest in the coordination of multiple AUVs. To address the requirements of coordinated missions, this paper proposes a comprehensive solution for the coordinated development of multi-AUV formations, encompassing long-range ferrying, coordinated detection, and surrounding attack. In the initial phase, detection devices are deactivated, employing a path planning method based on the Rapidly Exploring Random Tree (RRT) algorithm to ensure collision-free AUV movement. During the coordinated detection phase, an artificial potential field method is applied to maintain AUV formation integrity and avoid obstacles, dynamically updating environmental probability based on formation movement. In the coordinated surroundings attack stage, predictive capabilities are enhanced using Long Short-Term Memory (LSTM) networks and reinforcement learning. Specifically, LSTM forecasts the target’s position, while the Deep Deterministic Policy Gradient (DDPG) method controls AUV formation. The effectiveness of this coordinated solution is validated through an integrated simulation trajectory. Full article
(This article belongs to the Special Issue Underwater Navigation, Guidance and Control Technology in Ocean Engineering)
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