Affiliation:
1. Energy Systems Modelling (MSE) Laboratory, Mohamed Khider University, Biskra 07000, Algeria
2. College of Engineering and Information Technology, University of Dubai, Dubai 14143, United Arab Emirates
3. Laboratory of LI3C, Mohamed Khider University, Biskra 07000, Algeria
Abstract
The growing interest in unmanned aerial vehicles (UAVs) from both the scientific and industrial sectors has attracted a wave of new researchers and substantial investments in this expansive field. However, due to the wide range of topics and subdomains within UAV research, newcomers may find themselves overwhelmed by the numerous options available. It is therefore crucial for those involved in UAV research to recognize its interdisciplinary nature and its connections with other disciplines. This paper presents a comprehensive overview of the UAV field, highlighting recent trends and advancements. Drawing on recent literature reviews and surveys, the review begins by classifying UAVs based on their flight characteristics. It then provides an overview of current research trends in UAVs, utilizing data from the Scopus database to quantify the number of scientific documents associated with each research direction and their interconnections. This paper also explores potential areas for further development in UAVs, including communication, artificial intelligence, remote sensing, miniaturization, swarming and cooperative control, and transformability. Additionally, it discusses the development of aircraft control, commonly used control techniques, and appropriate control algorithms in UAV research. Furthermore, this paper addresses the general hardware and software architecture of UAVs, their applications, and the key issues associated with them. It also provides an overview of current open source software and hardware projects in the UAV field. By presenting a comprehensive view of the UAV field, this paper aims to enhance our understanding of this rapidly evolving and highly interdisciplinary area of research.
Funder
Laboratory of Energetic System Modelling (LMSE) of the University of Biskra, Algeria
General Directorate of Scientific Research and Technological Development (DGRSDT) in Algeria
Ministry of Higher Education and Scientific Research in Algeria
University of Dubai
Subject
Information Systems and Management,Computer Networks and Communications,Modeling and Simulation,Control and Systems Engineering,Software
Reference394 articles.
1. Face mask detection in smart cities using deep and transfer learning: Lessons learned from the COVID-19 pandemic;Himeur;Systems,2023
2. Kheddar, H., Himeur, Y., and Awad, A.I. (2023). Deep Transfer Learning Applications in Intrusion Detection Systems: A Comprehensive Review. arXiv.
3. Atalla, S., Daradkeh, M., Gawanmeh, A., Khalil, H., Mansoor, W., Miniaoui, S., and Himeur, Y. (2023). An Intelligent Recommendation System for Automating Academic Advising Based on Curriculum Analysis and Performance Modeling. Mathematics, 11.
4. An innovative deep anomaly detection of building energy consumption using energy time-series images;Copiaco;Eng. Appl. Artif. Intell.,2023
5. Next-generation energy systems for sustainable smart cities: Roles of transfer learning;Himeur;Sustain. Cities Soc.,2022
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