Multi UAV

Multi-UAV research focuses on coordinating multiple unmanned aerial vehicles (UAVs) to achieve complex tasks more efficiently and robustly than single UAVs. Current research emphasizes developing advanced algorithms for trajectory planning and collision avoidance, often employing reinforcement learning (particularly multi-agent RL), model predictive control, and graph-based methods, sometimes incorporating quantum computing for optimization. These advancements are crucial for diverse applications, including infrastructure inspection, search and rescue, environmental monitoring, and data collection in challenging environments, improving efficiency, safety, and scalability in these domains.