Quadrotor Flight

Quadrotor flight research focuses on developing robust and efficient control systems for these unmanned aerial vehicles, enabling complex maneuvers and autonomous navigation. Current efforts concentrate on advanced control algorithms, including model predictive control (MPC) for precise trajectory tracking during acrobatic flights, and neural networks, particularly end-to-end approaches, for learning energy-optimal control policies even in the presence of unmodeled dynamics. These advancements are crucial for expanding the capabilities of quadrotors in challenging environments and applications such as search and rescue, inspection, and delivery, improving both performance and autonomy.