UAV Trajectory Planning

UAV trajectory planning focuses on efficiently and safely generating optimal flight paths for unmanned aerial vehicles, considering factors like obstacle avoidance, communication constraints, and mission objectives. Current research emphasizes developing robust and computationally efficient algorithms, incorporating techniques like deep reinforcement learning, graph neural networks, and dynamic programming to address challenges in complex and dynamic environments. These advancements are crucial for improving the autonomy, reliability, and scalability of UAV applications across diverse sectors, including search and rescue, delivery, and network infrastructure. The field is also increasingly incorporating human-centric considerations and addressing the impact of environmental factors like weather on trajectory optimization.