Swarm satellite research results in AIAA Best Paper Award

11/17/2015 Susan Mumm, Aerospace Engineering

The award-winning paper presents a distributed, guidance and control algorithm for reconfiguring swarms composed of hundreds to thousands of spacecraft such as CubeSats and Femtosatellites, with limited communication and computation capabilities.

Written by Susan Mumm, Aerospace Engineering

Recent AE PhD Daniel Morgan and his advisor, CSL Associate Prof. Soon-Jo Chung, have won an American Institute of Aeronautics and Astronautics (AIAA) Best Paper Award for research on the guidance and control of swarm satellites.

The paper, “Swarm Assignment and Trajectory Optimization Using Variable-Swarm, Distributed Auction Assignment and Model Predictive Control,” was also co-authored with Dr. Fred Y. Hadaegh, Associate Chief Technologist of the Jet Propulsion Laboratory at the California Institute of Technology. The research was presented at the 2015 AIAA Guidance, Navigation, and Control (GNC) Conference.

This is the second AIAA Best Paper Award that Chung has garnered as a faculty member of aerospace engineering at Illinois.

The award will be presented on January 5, 2016, during the award and recognition luncheon held in conjunction with the AIAA Science and Technology Forum and Exposition (SciTech 2016) at the Manchester Grand Hyatt in San Diego, California.

Soon-Jo Chung
Soon-Jo Chung
Soon-Jo Chung
Chung directed Morgan’s graduate work, resulting in a master’s degree in 2011 and a PhD in 2015. Morgan now works as a senior guidance, control and navigation engineer at Space X in California. Chung noted “it is great to see that Dan’s hard work and innovative research in spacecraft swarms is rewarded by this best paper recognition. The AIAA GNC Conference is the largest controls conference in the aerospace community. “

The award-winning paper presents a distributed, guidance and control algorithm for reconfiguring swarms composed of hundreds to thousands of spacecraft such as CubeSats and Femtosatellites, with limited communication and computation capabilities. The SATO (Swarm Assignment and Trajectory Optimization) algorithm solves both the distributed auction-based optimal assignment and collision-free trajectory generation using sequential convex programming for swarms of spacecraft in an integrated manner, when given the desired shape of the swarm (without pre-assigned terminal positions).

Researchers also produced a video validating the algorithms. The NASA Space Technology Research Fellowship Program and JPL sponsored this research.


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This story was published November 17, 2015.