Towards intelligent, reliable UAV networks: commentary on “advances in unmanned aerial systems: technologies, applications, and challenges”
The low-altitude economy is transforming unmanned aerial vehicles into intelligent, networked agents. This commentary synthesizes the contributions of the Special Issue into four thematic areas. Health-management frameworks employ adaptive memory matrices, probabilistic diagnostics, and simulation to enable in-flight predictive maintenance. Perception and navigation systems fuse light detection and ranging data, intensity cues, vision, and inertial inputs to achieve Global Positioning System (GPS)-resilient localization and mapping in feature-sparse or degraded environments. Swarm communication combines decentralized multi-agent reinforcement learning with lightweight blockchain protocols to secure real-time policy exchange while balancing throughput, fairness, and energy efficiency. Resilient air-ground connectivity couples scenario-transfer neural channel models with joint trajectory and power optimization to sustain millimeter-wave links across diverse urban geometries. These advances outline an emerging unmanned aerial vehicle ecosystem, yet interoperable standards, trustworthy Artificial Intelligence (AI), renewable power integration, and large-scale field validation remain critical challenges to achieving truly scalable, autonomous, and sustainable operations.
Authors
- Ciyuan Chen (ORCID: https://orcid.org/0000-0003-2664-7817)
- Zhonghui Xu (ORCID: https://orcid.org/0000-0002-6469-9178)
- Xin Zhao (ORCID: https://orcid.org/0009-0000-7261-4480)
Institutions
- City University of Hong Kong (HK)
- Nanjing University of Aeronautics and Astronautics (CN)
Publication Details
- Journal
- Complex Engineering Systems
- Published
- 2025-09-30
- DOI
- https://doi.org/10.20517/ces.2025.55
- Citations
- 1
- Primary Topic
- UAV Applications and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 4.99
Funders
- National Natural Science Foundation of China
- Government of Jiangsu Province