VSCL’s Reinforcement Learning Control Law for Ground Target Tracking Featured in January’s Aerospace America

The January 2019 edition of Aerospace America’s annual Year in Review section for Information Systems featured the flight-demonstration of a machine learning algorithm developed by a team of VSCL students and faculty.  The article discussed the progression of the project from its first demonstration in December 2017 to more recent demonstrations.  The algorithm is based on Q-Learning and provides a control policy for the vehicle’s orientation in order to keep the target fixed in the image frame autonomously. The algorithm was tested against stationary and randomly moving targets in both a structured and unstructured environment.

The Aerospace America article can be found here.