Unmanned Vehicles Systems Application

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

Deadline for manuscript submissions: 15 October 2025 | Viewed by 1588

Special Issue Editors


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Guest Editor
Department of Electrical, Electronics and Telecommunication Engineering and Naval Architecture (DITEN), University of Genoa, 16145 Genoa, Italy
Interests: cognitive and AI-enabled radios; wireless communications; 5G/6G; UAV communications; V2X; self-awareness; bayesian filtering; semantic communications; active inference and artificial intelligence

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Guest Editor
School of Electronic Engineering and Computer Science Queen Mary University of London Mile End Road, London E1 4NS, UK
Interests: cognitive communications and networking; ML/AI in wireless communications; 5G/6G; emerging applications of cognitive communications and networking in verticals

Special Issue Information

Dear Colleagues,

The Unmanned Vehicles (UVs) market has grown and diversified, leading to increased commercial use, especially in civilian applications such as search and rescue operations, telecommunications, crop monitoring, aerial photography, environmental research, infrastructure inspection, delivery of goods, remote sensing, and disaster management. Unmanned Vehicles include Unmanned Ground Vehicles (UGVs), Unmanned Aerial Vehicles (UAVs), and Unmanned Underwater Vehicles (UUVs). These vehicles operate without a human on board and are controlled remotely, either through radio control or automated guidance using GNSS-based applications.

One of the key factors in ensuring the successful deployment of remotely piloted unmanned vehicles is the establishment of a reliable connection between the vehicle and its pilot. Wireless communication systems play a crucial role in this, and it is essential to select the right system to accommodate different missions with varying communication ranges and security needs.

The future of UVs is promising as they quickly progress towards autonomous operations. This transition signifies a significant technological advancement that is set to transform the unmanned vehicle industry. This special issue aims to showcase the recent advancements in technologies and algorithms designed to enhance the autonomy, reliability, and safety of UVs and cover their primary applications in the communication sector. Topics of interest include but are not limited to:

  • Navigation and control algorithms
  • Autonomy and decision-making
  • Perception and multi-sensor fusion
  • Networked swarms
  • Trajectory Planning
  • Resource allocation
  • Data collection
  • Network coverage
  • Positioning optimization
  • Physical layer security
  • AI-based jammer detection and anti-jamming
  • AI-based spoofer detection and anti-spoofing
  • Emerging applications of UAV communications

Dr. Ali Krayani
Dr. Atm Shafiul Alam
Guest Editors

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Keywords

  • unmanned aerial vehicles
  • navigation and control Autonomy
  • perception
  • decision-making
  • multiple-agent systems
  • networked swarms
  • reliability
  • safety
  • risk assessment
  • trajectory planning
  • resource allocation

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Published Papers (1 paper)

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Research

23 pages, 10712 KiB  
Article
A Multi-Sensor Fusion Autonomous Driving Localization System for Mining Environments
by Yi Wang, Chungming Own, Haitao Zhang and Minzhou Luo
Electronics 2024, 13(23), 4717; https://doi.org/10.3390/electronics13234717 - 28 Nov 2024
Viewed by 1315
Abstract
We propose a multi-sensor fusion localization framework for autonomous heavy-duty trucks suitable for mining scenarios, which enables high-precision, real-time trajectory generation, and map construction. The motion estimated through pre-integration of the inertial measurement unit (IMU) can eliminate distortions in the point cloud and [...] Read more.
We propose a multi-sensor fusion localization framework for autonomous heavy-duty trucks suitable for mining scenarios, which enables high-precision, real-time trajectory generation, and map construction. The motion estimated through pre-integration of the inertial measurement unit (IMU) can eliminate distortions in the point cloud and provide an initial guess for LiDAR odometry optimization. The point cloud information obtained from LiDAR can assist in recovering depth information from image features extracted by the monocular camera. To ensure real-time performance, we introduce an iKD-tree to organize the point cloud data. To address issues arising from bumpy road segments and long-distance driving in practical mining scenarios, we can incorporate a large number of relative and absolute measurements from different sources, such as GPS information and AprilTag-assisted localization data, including loop closure, as factors in the system. The proposed method has been extensively evaluated on public datasets and self-collected datasets from mining sites. Full article
(This article belongs to the Special Issue Unmanned Vehicles Systems Application)
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