UAV Swarm and Multi-UAV Systems: Cooperative Control, Distributed Intelligence and Applications
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: 15 February 2027 | Viewed by 26
Editors
Interests: distributed reasoning; data center network; deep learning algorithms; time-sensitive networks
Interests: wireless communication and mobile computing; industrial cyber–physical system and intelligent control; edge intelligence; digital twin network
Special Issues, Collections and Topics in MDPI journals
Interests: networked unmanned systems; cognitive decision-making; multimodal interaction for embodied agents; semantic communication; autonomous driving networks; network intelligence/intelligent networking
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
UAV swarms and multi-UAV systems are core technologies for low-altitude economies. The advancement of UAV swarms and multi-UAV systems is transitioning from fundamental coordination to sophisticated, intelligent collaboration. These systems are poised to revolutionize applications ranging from smart city management and emergency response to infrastructure inspection and environmental monitoring. These multi-UAV scenarios require efficient cooperative control, reasonable task allocation, real-time path planning, collaborative computing, and distributed intelligence to achieve reliable autonomous collaboration under complex and communication-constrained environments.
This Special Issue focuses on cooperative control, task allocation, path planning, collaborative computing, optimization, and distributed intelligence for UAV swarm and multi-UAV systems. It aims to collect innovative theories, algorithms, architectures, and engineering implementations that support reliable and efficient multi-UAV collaboration in typical urban and industry applications.
This Special Issue complements existing publications in several important ways. It places a strong emphasis on practical, scenario-driven solutions tailored to smart cities, emergency rescue, power inspection, forest monitoring, and intelligent transportation. It also highlights distributed learning and collaborative computing to address real-world constraints and enable reliable deployment of UAV swarm systems. We welcome high-quality original research articles, review articles, and communications covering recent advances in theories, algorithms, systems, and applications.
We look forward to receiving your contributions.
Dr. Tong Zhang
Prof. Dr. Changyan Yi
Prof. Dr. Kun Zhu
Guest Editors
Manuscript Submission Information
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Keywords
- UAV swarm
- multi-UAV systems
- cooperative control
- task allocation
- path planning
- collaborative computing
- optimization
- distributed intelligence
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