Abstract
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. © The Author(s) 2025.
| Original language | English |
|---|---|
| Article number | 14 |
| Number of pages | 10 |
| Journal | Complex Engineering Systems |
| Volume | 5 |
| Issue number | 3 |
| Online published | 30 Sept 2025 |
| DOIs |
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| Publication status | Published - 2025 |
Funding
This work is supported by the National Natural Science Foundation of China under grants 62402221; the Science Foundation of Jiangsu Province under Grant BK20241379.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 17 Partnerships for the Goals
Research Keywords
- air-ground link
- autonomous navigation
- health assessment
- UAV swarm
- Unmanned aerial vehicles (UAVs)
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