Autonomous Quadrotor

Autonomous quadrotors are unmanned aerial vehicles capable of independent flight and navigation, primarily aimed at achieving agile maneuvers and safe operation in complex environments. Current research heavily emphasizes robust control strategies, often employing reinforcement learning and model predictive control algorithms, to address challenges like aerodynamic disturbances, sensor noise, and cyber-attacks. These advancements are significant for applications ranging from search and rescue to high-speed drone racing and security, pushing the boundaries of both robotics and control systems.