The Development of Dynamic Guidance and Navigation Algorithms for Autonomous On-Orbit Multi-Satellite Aggregation
Research Paper

The Development of Dynamic Guidance and Navigation Algorithms for Autonomous On-Orbit Multi-Satellite Aggregation

November 28, 2019

David A. Barnhart, Ryan H. Duong, Lizvette Villafaña, Jaimin Patel & Shreyash Annapureddy in 70th International Astronautical Congress (IAC), Washington D.C., United States, 21-25 October 2019.


"With the growing popularity of low-cost satellite missions merged with the ability to potentially rendezvous and “connect” on orbit, the potential to enable mission objectives typically reserved for very large monolithic satellites with many small low-cost satellites arises not just in swarm flight but through the possibility of on-orbit satellite “aggregation”. Ultimately, such satellite aggregation concepts, resulting in a new singular spacecraft comprised from many individual functioning elements, must adhere to basic spacecraft design considerations like attitude control and thermal management upon aggregation/integration. When considering on-orbit operations, an autonomous methodology must be implemented to ensure seamless spacecraft functionality and control through aggregation. The University of Southern California Information Sciences Institute (USC ISI) and Space Engineering Research Center (SERC) have fabricated multiple modular pseudosatellite prototypes and developed an autonomous GNC reconfiguration algorithm to redefine a singular reaction control system from multiple contributing spacecraft. These prototypes, bounded by 3 degrees of freedom on a frictionless airbearing table, perform individual maneuvers with 8 body mounted thrusters to simulate rendezvous and proximity operations (RPO) docking and aggregation. Upon aggregation an integrated algorithm demonstrates autonomous reconfiguration of the aggregate platforms thrusters and execute additional maneuvers with its new control orientation. In parallel, the SERC team created a simulation environment, which enables additional virtual aggregation to show scale of the algorithm’s capability in optimizing aggregated GNC subsystem for up to “N” number of elements. This paper will present preliminary results of the first set of algorithmic experimentation in active autonomous GNC reconfiguration."

Keywords:  Aggregation, GNC, cellular morphology

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