Autonomous Navigation of Unmanned Maritime Vehicles

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 2129

Special Issue Editors


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Guest Editor
College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China
Interests: unmanned surface vehicle; intelligent decision; nonlinear control
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Guest Editor
College of Information Engineering, Henan University of Science and Technology, Luoyang 471000, China
Interests: autonomous collision avoidance of unmanned vehicles
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 256600, China
Interests: unmanned vehicles and their automatic control

Special Issue Information

Dear Colleagues,

With the continuous development and progress of science and technology, unmanned systems have gradually become a research hotspot in the field of machine intelligence. Under the background of artificial intelligence, big data and the Internet of Things, ocean vehicles represented by ships are gradually developing towards modularization, intelligence and unmanned characteristics. Unmanned maritime vehicles have become the focus and development trend of the industry.

However, there is still a long way to go to fully realize the autonomous navigation of unmanned maritime vehicles, despite the progress that has been made. Among all the core technologies, state detection, environment awareness, communication navigation and other technologies are relatively mature and have been applied in practice. The realization of many “advanced” functions such as autonomous navigation, safety early warning and intelligent collision avoidance still requires more scientific research efforts. This Special Issue aims to address issues involved in the analysis, design, and implementation of Autonomous Navigation of Unmanned Maritime Vehicles. This includes:

  1. Intelligent agents and multi-agent systems;
  2. Intelligent control of ships and ocean vehicles;
  3. Intelligent perception and autonomous control of unmanned systems;
  4. Multi-agent systems and intelligent transportation network control;
  5. Intelligent control and detection technology;
  6. Autonomous navigation control of surface or underwater vehicles;
  7. Nonlinear control;
  8. Unmanned systems;
  9. Autonomous control of robots;
  10. Information collection of ships or unmanned craft;
  11. Ship or unmanned craft control technology;
  12. Image processing techniques;
  13. Field verification of unmanned systems;
  14. Development trend of unmanned systems in the future.

Dr. Dongdong Mu
Dr. Xiaojie Sun
Dr. Cunhe Li
Guest Editors

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Published Papers (1 paper)

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Research

25 pages, 13882 KiB  
Article
Localization Method for Underwater Robot Swarms Based on Enhanced Visual Markers
by Qingbo Wei, Yi Yang, Xingqun Zhou, Chuanzhi Fan, Quan Zheng and Zhiqiang Hu
Electronics 2023, 12(23), 4882; https://doi.org/10.3390/electronics12234882 - 4 Dec 2023
Cited by 2 | Viewed by 1674
Abstract
In challenging tasks such as large-scale resource detection, deep-sea exploration, prolonged cruising, extensive topographical mapping, and operations within intricate current regions, AUV swarm technologies play a pivotal role. A core technical challenge within this realm is the precise determination of relative positions among [...] Read more.
In challenging tasks such as large-scale resource detection, deep-sea exploration, prolonged cruising, extensive topographical mapping, and operations within intricate current regions, AUV swarm technologies play a pivotal role. A core technical challenge within this realm is the precise determination of relative positions among AUVs within the cluster. Given the complexity of underwater environments, this study introduces an integrated and high-precision underwater cluster positioning method, incorporating advanced image restoration algorithms and enhanced underwater visual markers. Utilizing the Hydro-Optical Image Restoration Model (HOIRM) developed in this research, image clarity in underwater settings is significantly improved, thereby expanding the attenuation coefficient range for marker identification and enhancing it by at least 20%. Compared to other markers, the novel underwater visual marker designed in this research elevates positioning accuracy by 1.5 times under optimal water conditions and twice as much under adverse conditions. By synthesizing the aforementioned techniques, this study has successfully developed a comprehensive underwater visual positioning algorithm, amalgamating image restoration, feature detection, geometric code value analysis, and pose resolution. The efficacy of the method has been validated through real-world underwater swarm experiments, providing crucial navigational and operational assurance for AUV clusters. Full article
(This article belongs to the Special Issue Autonomous Navigation of Unmanned Maritime Vehicles)
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