Autonomous Self Organized UAV Swarm Systemis

Abstract

Interest in Self-Organized (SO) unmanned aerial vehicles (UAVs) systems is increasing because of their flexibility, versatility and economics. Many countries and industries are developing autonomous and swarming UAVs for reconnaissance, surveillance, intelligence gathering, and target engagement and neutralization. The processes for effectively developing these systems are still in their infancy. Currently, little effort is focused on building simple agent rules with low-level SO systems communication in order to facilitate emergent behaviors. Note that only with the use of effective control structures can the full potential of these systems realized. Presented is an innovative new paradigm for developing SO-based autonomous vehicles. Using a formal design model, the Interactive Partially Observable Markov Decision Process, a full understanding of this SO domain is possible. With this design model and a focused effort on the minimization of computational and informational complexity, emergent entangled control hierarchies allow the SO rules to operate efficiently and effectively. This work extends the formal model decomposition technique, and in doing so ties in the information theoretic optimization to develop emergent structures. Preliminary computational results reflect limited success.