Cited by 295UAV Applications and OptimizationDistributed Control Multi-Agent SystemsRobotic Path Planning Algorithms

Design Challenges of Multi-UAV Systems in Cyber-Physical Applications: A Comprehensive Survey and Future Directions

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Shakeri, Reza, Al-Garadi, Mohammed Ali, Badawy, Ahmed, Mohamed, Amr, Khattab, Tamer, Al-Ali, Abdulla Khalid, Harras, Khaled A., Guizani, Mohsen·2019·IEEE Communications Surveys & Tutorials

Abstract

Unmanned aerial vehicles (UAVs) have recently rapidly grown to facilitate a wide range of innovative applications that can fundamentally change the way cyber-physical systems (CPSs) are designed. CPSs are a modern generation of systems with synergic cooperation between computational and physical potentials that can interact with humans through several new mechanisms. The main advantages of using UAVs in CPS application is their exceptional features, including their mobility, dynamism, effortless deployment, adaptive altitude, agility, adjustability, and effective appraisal of real-world functions anytime and anywhere. Furthermore, from the technology perspective, UAVs are predicted to be a vital element of the development of advanced CPSs. Therefore, in this survey, we aim to pinpoint the most fundamental and important design challenges of multi-UAV systems for CPS applications. We highlight key and versatile aspects that span the coverage and tracking of targets and infrastructure objects, energy-efficient navigation, and image analysis using machine learning for fine-grained CPS applications. Key prototypes and testbeds are also investigated to show how these practical technologies can facilitate CPS applications. We present and propose state-of-the-art algorithms to address design challenges with both quantitative and qualitative methods and map these challenges with important CPS applications to draw insightful conclusions on the challenges of each application. Finally, we summarize potential new directions and ideas that could shape future research in these areas.

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Crossref · 10.1109/comst.2019.2924143

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Authors
Shakeri, R., Al-Garadi, M. A., Badawy, A., Mohamed, A., Khattab, T., Al-Ali, A. K., Harras, K. A., & Guizani, M.
Affiliations
  • Qatar University (QA)
  • Carnegie Mellon University Qatar (QA)
Venue
IEEE Communications Surveys & Tutorials
Published
2019
Volume
21
Issue
4
Pages
3340-3385
ISSN
  • 1553-877X (ISSN-L)
  • 2373-745X
OpenAlex
W2897490830
Cited by
295
References
7
Citations by year
2026: 33 · 2025: 44 · 2024: 33 · 2023: 31 · 2022: 51 · 2021: 58 · 2020: 34 · 2019: 11
FWCI
28.32
Type
journal article
Language
en
Open access
Locations
  • IEEE Communications Surveys & Tutorials (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • Qatar University QSpace (Qatar University) (submittedVersion)
  • arXiv (Cornell University)
Funders
Qatar University (QUCP-CENG-2018\2019-1)
Topics
  • Physical Sciences › Engineering › Aerospace Engineering › UAV Applications and Optimization
  • Physical Sciences › Computer Science › Computer Networks and Communications › Distributed Control Multi-Agent Systems
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Robotic Path Planning Algorithms
Keywords
multi-UAV systems, unmanned aerial vehicles, cyber-physical systems, target tracking, infrastructure monitoring, energy-efficient navigation, machine learning image analysis, UAV prototype

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