Alternative control methodologies for patrolling assets with unmanned air vehicles

Abstract

We consider the problem of controlling a system of many Unmanned Air Vehicles (UAVs) whose mission is to patrol and protect a set of important assets on the ground. We present two widely differing methods, employing emergent intelligent swarms and closed-form optimization. The optimization approach assumes complete communication of all newly sensed information among all of the UAVs as it becomes available. The optimization problem is a network flow model that is readily solvable to obtain optimum task allocations to configure patrols for the UAVs in the swarm. Reapplication of the optimization algorithm upon demand yields the benefit of cooperative feedback control. The swarm procedure establishes patrol patterns by utilizing decentralized, reactive, behaviors. Global communication is unnecessary, and control is established only through passive sensors and minimal short-range radio communication. Both models have been implemented and successfully demonstrated in an agent-based, simulated environment. The strengths, weaknesses, and relative performance the two approaches are compared and discussed. © 2007 Springer-Verlag Berlin Heidelberg.