Patent for AI-Powered Control of Drone Networks
ECE William Lincoln Smith Professor Tommaso Melodia and Associate Research Professor Salvatore D’Oro were awarded a patent for “Distributed deep reinforcement learning framework for software-defined unmanned aerial vehicle network control.”
Abstract Source: USPTO
Provided herein are systems for controlling a network of distributed non-terrestrial nodes including a control framework operative to train and control a plurality of the non-terrestrial nodes, the control framework including a control interface in communication with a network operator to receive one or more specified control objectives, and a learning engine operative to train a virtual non-terrestrial network, wherein the control framework is further operative to transfer knowledge gained through the training of the virtual non-terrestrial network to the network of distributed non-terrestrial nodes as data-driven logic unit configurations tailored for the specified control objectives.
