UAV Swarm
UAV swarms, groups of unmanned aerial vehicles working collaboratively, are being actively researched for applications like environmental monitoring, search and rescue, and data collection. Current research focuses on developing decentralized control algorithms, often inspired by natural swarm behavior, and employing machine learning techniques like reinforcement learning and deep neural networks for tasks such as path planning, collision avoidance, and cooperative perception. These advancements are improving the efficiency, robustness, and autonomy of UAV swarms, leading to significant potential for diverse practical applications and driving innovation in distributed systems and AI.
Papers
UAV Virtual Antenna Array Deployment for Uplink Interference Mitigation in Data Collection Networks
Hongjuan Li, Hui Kang, Geng Sun, Jiahui Li, Jiacheng Wang, Xue Wang, Dusit Niyato, Victor C. M. Leung
A Scalable Decentralized Reinforcement Learning Framework for UAV Target Localization Using Recurrent PPO
Leon Fernando, Billy Pik Lik Lau, Chau Yuen, U-Xuan Tan