New Technologies in Autonomous 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: closed (1 May 2023) | Viewed by 2355

Special Issue Editor


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Guest Editor
Norwegian Defence Research Establishment, NO-2027 Kjeller, Norway
Interests: synthetic aperture sonar; autonomous underwater vehicles; oceanographic techniques; sonar; sonar imaging; synthetic aperture radar; bathymetry; carbon capture and storage; echo; image filtering; image resolution; inertial

Special Issue Information

Dear Colleagues,

Autonomous underwater vehicles (AUVs) have, in the last decades become the standard tool for many maritime applications. They are a safe, cost-effective and reliable alternative to many manned or remotely controlled systems. Typical applications have been seafloor mapping, pipeline inspection and mine counter measures. As the user experience has grown, the demand for improved autonomy, endurance, robustness and sensors has increased rapidly. Lately, there have also been a surge of new applications where AUVs have been used, such as under ice operations, search for sunken debris, sea wreck inspection and submarine surveillance.

To reach the AUVs potential for operating fully autonomously in extreme environments, while simultaneously collecting data with unprecedented resolution and quality, there is a strong demand for further novelty and customization within AUV technology.

This special issue aims to publish new research in the field of Autonomous Underwater Vehicles.

Topics of this special issue will include, but are not limited to:

  • Vehicle design
  • New applications, both civilian and military
  • Multi-static operations
  • Robustness, safety and risk management
  • Energy supply
  • Autonomy and mission planning
  • Automated data analysis
  • Communication
  • Navigation
  • Sensors: optical, acoustic, chemical
  • Synthetic aperture sonar
  • Machine Learning methods for AUVs

Dr. Torstein Olsmo Saebo
Guest Editor

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Keywords

  • vehicle design
  • new applications, both civilian and military
  • multi-static operations
  • robustness, safety and risk management
  • energy supply
  • autonomy and mission planning
  • automated data analysis
  • communication
  • navigation
  • sensors: optical, acoustic, chemical
  • synthetic aperture sonar
  • machine learning methods for AUVs

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Published Papers (1 paper)

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Research

23 pages, 1039 KiB  
Article
PROMETHEE-Based Multi-AUV Threat Assessment Method Using Combinational Weights
by Dan Yu, Hongjian Wang, Benyin Li, Zhao Wang, Jingfei Ren and Xiaoning Wang
J. Mar. Sci. Eng. 2023, 11(7), 1422; https://doi.org/10.3390/jmse11071422 - 15 Jul 2023
Cited by 1 | Viewed by 1281
Abstract
The assessment of multiple incoming autonomous underwater vehicles (multi-AUVs) and threat prioritization are critical to underwater defense. To solve problems troubling multi-AUV threat assessment solutions, such as difficult data analysis, high subjectivity, and rigid prioritization logic, we propose the PROMETHEE algorithm based on [...] Read more.
The assessment of multiple incoming autonomous underwater vehicles (multi-AUVs) and threat prioritization are critical to underwater defense. To solve problems troubling multi-AUV threat assessment solutions, such as difficult data analysis, high subjectivity, and rigid prioritization logic, we propose the PROMETHEE algorithm based on fusion weights calculated twice by entropy and an analytic network process (ANP), respectively. First, according to AUV detection performance and underwater confrontation situation analysis, the main criteria and indicators of threat assessment are determined. The threat assessment system is provided by unified measurement of these indicators. Then, through analysis and assessment, the weighting algorithm is designed using entropy and ANP. The subjective weight calculated based on ANP and the objective weight obtained based on the entropy method are fused twice to obtain the combined weights, and the influence of subjective and objective factors on problem analysis is considered. Finally, by analyzing the simulation results of a multi-AUV, it is proven that the proposed algorithm is scientific and effective for AUV threat assessment. According to the experimental results, accurate evaluation of the target improved by at least 10%, enabling delivery of results close to the real confrontation situation with high reliability. Full article
(This article belongs to the Special Issue New Technologies in Autonomous Underwater Vehicles)
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