Jonathan Sprinkle

Research Experience: Autonomous Vehicles

Capture definitions for a pursuit/evasion game between fixed-wing aircraft (colloquially known as a dogfight).

Unmanned Aerial Vehicles (UAVs)

SEC Capstone Demonstrations: in conjunction at Berkeley with J. Mikael Eklund, Shankar Sastry, H. Jin Kim

I joined the SEC project during its final year, and participated in the Capstone Demonstration by participating in the design and implementation of two experiments in the demonstration, each of which was flown on a live aircraft in June 2004 at Edwards AFB. SEC was the DARPA Software Enabled Control project, headed by Program Manager Dr. John Bay.

Pursuit Evasion Games

This demonstration involved the development of a model predictive controller that tracked a final waypoint, as well as avoided a moving pursuit aircraft through the same controller. The timescale of this project was about 6 months. We successfully demonstrated the algorithms and code against a trained pilot, who was flying an F-15 (see videos below).

This MPG movie is of a symmetric PEG between our UAV (Yellow) and our adversary F-15 (Blue), which is piloted by a human.

This MPG movie is of a "chicken" game, where the adversary F-15 pulls out all the stops, and flies at maximum speed toward our speed-restricted aircraft, to see how long we can last before capture in a worst case scenario.

The project was performed with much advice from and thanks to John Hauser (University of Colorado, Boulder) and Richard Murray (Caltech).

Related Papers:

J. Mikael Eklund, Jonathan Sprinkle, S. Shankar Sastry, "Implementing and Testing a Nonlinear Model Predictive Tracking Controller for Aerial Pursuit Evasion Games on a Fixed Wing Aircraft", Proceedings of American Control Conference (ACC) 2005, 1509--1514, Portland, OR, Jun., 8--10, 2005.
Jonathan Sprinkle, J. Mikael Eklund, H. Jin Kim, S. Shankar Sastry, "Encoding Aerial Pursuit/Evasion Games with Fixed Wing Aircraft into a Nonlinear Model Predictive Tracking Controller", Proceedings of the 43rd IEEE Conference on Decision and Control, vol. 3, 2609--2614, Nassau, Bahamas, Dec., 14--17, 2004.

Guarantee of safe UAV landing.

This demonstration involved the calculation of safe sets which described the regions of the UAV statespace (3-D position, 3-D attitude, and velocity) from which a UAV could safely land on a runway. We used level-set methods as our model of computation for the reachable sets, and generated them offline using a toolbox. Once we had the level sets, we transformed them into an executable which ran at runtime to give real-time decisions of safety.