Aerial Vehicle Navigation

Aerial vehicle navigation research focuses on enabling autonomous unmanned aerial vehicles (UAVs) to safely and efficiently navigate diverse environments, often without relying on GPS. Current efforts concentrate on robust perception using LiDAR, cameras, and inertial measurement units, coupled with advanced planning algorithms like RRT*, DWA, and deep reinforcement learning for obstacle avoidance and trajectory optimization. These advancements are crucial for expanding UAV applications in areas like search and rescue, infrastructure inspection, and delivery, while also addressing critical safety and security concerns through methods like control barrier functions and encrypted communication.