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Intelligent Unmanned Aerial Vehicle (UAV): Flight Control and Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: 20 August 2025 | Viewed by 1914

Special Issue Editor


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Guest Editor
Konkuk Aerospace Design-Airworthiness Institute (KADA), Konkuk University, Seoul 05029, Republic of Korea
Interests: aircraft design; flight simulation and control; urban air mobility; unmanned aerial vehicles; design optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The upcoming Special Issue of Applied Sciences is dedicated to the cutting-edge technologies related to intelligent unmanned aerial vehicles (UAV), flight management and control. This edition brings together groundbreaking research and advancements in the area of UAV technology, focusing on the integration of flight dynamics and simulation, artificial intelligence, machine learning, and sophisticated control algorithms to enhance autonomy, efficiency, and safety. Contributions from leading experts and researchers worldwide delve into topics such as adaptive control strategies, real-time decision-making algorithms, swarm intelligence applications, human–machine interaction and collaboration, and other related topics. This Special Issue promises to be a pivotal resource for academics, engineers, and practitioners, offering a comprehensive overview of the latest innovations and challenges.

Prof. Dr. Maxim Tyan
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. Applied Sciences 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 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

  • decision making
  • flight control
  • swarm intelligence
  • flight dynamics
  • autonomy
  • operations

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Published Papers (1 paper)

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Research

15 pages, 4373 KiB  
Article
Application Strategy of Unmanned Aerial Vehicle Swarms in Forest Fire Detection Based on the Fusion of Particle Swarm Optimization and Artificial Bee Colony Algorithm
by Xiaohong Yan and Renwen Chen
Appl. Sci. 2024, 14(11), 4937; https://doi.org/10.3390/app14114937 - 6 Jun 2024
Cited by 3 | Viewed by 1515
Abstract
Unmanned aerial vehicle (UAV) swarm intelligence technology has shown unique advantages in agricultural and forestry disaster detection, early warning, and prevention with its efficient and precise cooperative operation capability. In this paper, a systematic application strategy of UAV swarms in forest fire detection [...] Read more.
Unmanned aerial vehicle (UAV) swarm intelligence technology has shown unique advantages in agricultural and forestry disaster detection, early warning, and prevention with its efficient and precise cooperative operation capability. In this paper, a systematic application strategy of UAV swarms in forest fire detection is proposed, including fire point detection, fire assessment, and control measures, based on the fusion of particle swarm optimization (PSO) and the artificial bee colony (ABC) algorithm. The UAV swarm application strategy provides optimized paths to quickly locate multiple mountain forest fire points in 3D forest modeling environments and control measures based on the analysis of the fire situation. This work lays a research foundation for studying the precise application of UAV swarm technology in real-world forest fire detection and prevention. Full article
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