Date of Award
Master of Science
Department of Electrical and Computer Engineering
Gary B. Lamont, PhD
This investigation uses a self-organization (SO) approach to enable cooperative search and destruction of retaliating targets with swarms of homogeneous and heterogeneous unmanned aerial vehicles (UAVs). To facilitate specific system design, a facilitating SO algebraic framework is created that emphasizes scalability, robustness, and flexibility. This framework is then used to implement a UAV behavior architecture relying upon rules governing formation and target interaction. Sets of applicable behaviors are created by weighted summation of the rules where different weights act as distinct behavior archetypes. Appropriate behavior archetypes are based upon sense information distilled from the environment and a simple perceptron mapping. Successful behaviors are evolved within this architecture using a genetic algorithm. This approach tests a swarm of UAVs, when sensor and attack abilities are both homogeneous and heterogeneous, against targets with superior engagement range. Resulting behaviors are highly cooperative, generally scaleable, and robust.
DTIC Accession Number
Price, Ian C., "Evolving Self-Organized Behavior for Homogeneous and Heterogeneous UAV or UCAV Swarms" (2006). Theses and Dissertations. 3465.