Game Theory and Biology Inspired Flight Control for Autonomous UAVs Operating in Contested Environments

Abstract

A self-organizing swarm of autonomous unmanned areal vehicles (UAVs) can provide a quick response to cyber-attacks in austere civilian and military environments. However, if a UAV swarm relies on centralized control, synchronization of swarm members, pre-planned actions or rule-based systems, it may not provide adequate and timely response against cyber attacks. We introduce game theory (GT) and biology inspired flight control algorithms to be run by each autonomous UAV to detect, localize and counteract rogue electromagnetic signal emitters. Each UAV positions itself such that the swarm tracks mobile adversaries while maintaining uniform node distribution and connectivity of the mobile ad-hoc network (MANET). UAVs use only their respective local neighbor information to determine their individual actions. Simulation experiments in OPNET show that our algorithms can provide an adequate area coverage over mobile interference sources. Our solution can be employed for civilian and military applications that require agile responses in dynamic environments.