Title :
GA Directed Self-Organized Search and Attack UAV Swarms
Author :
Price, Ian C. ; Lamont, Gary B.
Author_Institution :
Dept. of Electr. & Comput. Eng., Air Force Inst. of Technol., Dayton, OH
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
Keywords :
aerospace robotics; aircraft; genetic algorithms; mobile robots; multi-robot systems; remotely operated vehicles; self-adjusting systems; autonomous multi-UAV systems; directed self-organized search; genetic algorithm; swarm behavior; Aircraft; Biological system modeling; Computational modeling; Engineering management; Humans; Neural networks; System testing; Technology management; Unmanned aerial vehicles; Velocity control;
Conference_Titel :
Simulation Conference, 2006. WSC 06. Proceedings of the Winter
Conference_Location :
Monterey, CA
Print_ISBN :
1-4244-0500-9
Electronic_ISBN :
1-4244-0501-7
DOI :
10.1109/WSC.2006.323229
