GA directed self-organized search and attack UAV swarms

Authors:
Ian C. Price;Gary B. Lamont
Affiliations:
Graduate School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, Dayton, OH;Graduate School of Engineering and Management, Air Force Institute of Technology, Wright-Patterson AFB, Dayton, OH
Venue:
Proceedings of the 38th conference on Winter simulation
Year:
2006

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Abstract

Self-organization offers many potential benefits to autonomous multi-UAV systems. This research investigates the use of a self-organization (SO) framework for evolving UAV swarm behavior. This SO framework is used to design a UAV swarm simulation with evolving behavior. The swarm behavior is then evolved using a genetic algorithm (GA) to successfully locate and destroy retaliating stationary targets. This system is tested using both a set of strictly homogeneous UAVs and heterogeneous UAVs with intriguing results.