A deep learning and model predictive control framework to control quadrotors and agile robots

In recent years, computer scientists have developed increasingly advanced algorithms for controlling the movements of robotic agents. These include model predictive control (MPC) techniques, which use a model of the agent’s dynamics to optimize its future behavior toward a given goal while simultaneously satisfying a number of constraints (e.g., cannot crash into obstacles).