Advances in UAV Technology: Dynamics, Guidance, Navigation, and Control of Transformative Aerial Vehicles

A special issue of Aerospace (ISSN 2226-4310). This special issue belongs to the section "Aeronautics".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 1334

Special Issue Editors


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Guest Editor
Department Aerospace Engineering, Technical School of Engineering, University of Sevilla, 41092 Seville, Spain
Interests: guidance; navigation and control of aerospace vehicles; nonlinear control; intelligent systems; neural networks; singular perturbations; aircraft design

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Guest Editor
Department of Electronic Engineering, Universidade Federal de Minas Gerais, Belo Horizonte BR-31270901, MG, Brazil
Interests: nonlinear control; robust control; optimal control; predictive control; set-based estimation; autonomous vehicles; unmanned aerial vehicles; underactuated systems

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Guest Editor
Department of Electrical Engineering, Universidade Federal de Minas Gerais, Belo Horizonte BR-31270901, MG, Brazil
Interests: optimal control; robust control; robotics; convertible UAVs; modelling of mechanical systems

E-Mail Website
Guest Editor
Department of Electronic Engineering, Universidade Federal de Minas Gerais, Belo Horizonte BR-31270901, MG, Brazil
Interests: automatic control; tracking control; robust control; optimal control; robotics; motion planning

Special Issue Information

Dear Colleagues,

As we venture further into the era of unmanned aerial vehicles (UAVs), we encounter a landscape rich with innovation and versatility. This Special Issue is dedicated to exploring the cutting-edge advancements in UAV systems that push the boundaries of their capabilities. From convertible UAVs that seamlessly transition between flight modes, and bio-inspired designs that draw from the ingenuity of nature, to the pioneering unmanned underwater and aerial vehicles, this issue aims to be at the forefront of UAV evolution.

The core of this Special Issue lies in the advanced dynamics, guidance, navigation, and control (GNC) systems that empower these UAVs to perform with unprecedented efficiency and autonomy. We seek contributions that delve into the following:

  • Control Systems: Innovations in UAV control mechanisms that enhance stability, agility, and responsiveness.
  • Guidance Strategies: Advanced algorithms and techniques for precise UAV guidance in complex environments.
  • Navigation and Localization: Cutting-edge solutions for accurate UAV positioning, including GPS-based and GPS-denied environments.
  • Full Flight Envelope and Convertible UAVs: Research on UAVs capable of operating across the full spectrum of flight conditions, including transitional designs.
  • Unmanned Aircraft System Traffic Management (UTM): Insights into the integration of UAVs within the airspace management frameworks, ensuring safe and efficient operations.
  • eVTOL Technology: Developments in electric Vertical Take-Off and Landing (eVTOL) systems that are shaping the future of urban air mobility.
  • Distributed UAV Networks: Studies on the coordination and control of multiple UAVs working in tandem for complex tasks.
  • Applications: Innovative applications of UAV technology in surveillance, delivery, environmental monitoring, and more.
  • Path Planning: Techniques and algorithms for efficient route planning that consider environmental and regulatory constraints.
  • Mathematical Modelling: Theoretical and computational models that underpin the design and operation of advanced UAV systems.
  • High fidelity simulation environments: Computational environments that emulate UAV behaviors for testing control strategies and embedded electronic systems.

Prof. Dr. Sergio Esteban
Dr. Guilherme V. Raffo
Dr. Daniel Neri Cardoso
Dr. Marcelo Alves Dos Santos
Guest Editors

Manuscript Submission Information

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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. Aerospace 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 2400 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

  • unmanned aerial vehicles (UAVs)
  • innovative UAV design
  • UAV dynamics
  • guidance systems
  • navigation technologies
  • control mechanisms
  • convertible UAVs
  • bio-inspired UAVs
  • unmanned underwater and aerial vehicles
  • eVTOL (electric Vertical Take-Off and Landing)
  • unmanned aircraft system traffic management (UTM)
  • distributed UAV networks
  • UAV path planning
  • mathematical modeling in UAVs
  • UAV applications
  • localization and mapping

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Published Papers (1 paper)

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Research

29 pages, 3153 KiB  
Article
Towards Autonomous Operation of UAVs Using Data-Driven Target Tracking and Dynamic, Distributed Path Planning Methods
by Jae-Young Choi, Rachit Prasad and Seongim Choi
Aerospace 2024, 11(9), 720; https://doi.org/10.3390/aerospace11090720 - 3 Sep 2024
Viewed by 822
Abstract
A hybrid real-time path planning method has been developed that employs data-driven target UAV trajectory tracking methods. It aims to autonomously manage the distributed operation of multiple UAVs in dynamically changing environments. The target tracking methods include a Gaussian mixture model, a long [...] Read more.
A hybrid real-time path planning method has been developed that employs data-driven target UAV trajectory tracking methods. It aims to autonomously manage the distributed operation of multiple UAVs in dynamically changing environments. The target tracking methods include a Gaussian mixture model, a long short-term memory network, and extended Kalman filters with pre-specified motion models. Real-time vehicle-to-vehicle communication is assumed through a cloud-based system, enabling virtual, dynamic local networks to facilitate the high demand of vehicles in airspace. The method generates optimal paths by adaptively employing the dynamic A* algorithm and the artificial potential field method, with minimum snap trajectory smoothing to enhance path trackability during real flights. For validation, software-in-the-loop testing is performed in a dynamic environment composed of multiple quadrotors. The results demonstrate the framework’s ability to generate real-time, collision-free flight paths at low computational costs. Full article
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