Drone Control

Drone control research focuses on developing robust and intuitive methods for autonomous and semi-autonomous flight, aiming to improve safety, efficiency, and ease of use. Current efforts concentrate on advanced control algorithms like model predictive control (MPC) and deep reinforcement learning (DRL), often incorporating techniques such as Proximal Policy Optimization (PPO) and Siamese networks, to handle complex environments and diverse mission objectives. These advancements are significant for expanding drone applications in areas like infrastructure inspection, search and rescue, and delivery, while also improving human-machine interaction through voice commands, haptic feedback, and augmented reality interfaces.