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Alternative Control Methodologies for Patrolling Assets With Unmanned Air Vehicles

In: Cooperative Systems

Author

Listed:
  • Kendall E. Nygard

    (North Dakota State University)

  • Karl Altenburg

    (North Dakota State University)

  • Jingpeng Tang

    (North Dakota State University)

  • Doug Schesvold

    (North Dakota State University)

  • Jonathan Pikalek

    (North Dakota State University)

  • Michael Hennebry

    (North Dakota State University)

Abstract

Summary 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.

Suggested Citation

  • Kendall E. Nygard & Karl Altenburg & Jingpeng Tang & Doug Schesvold & Jonathan Pikalek & Michael Hennebry, 2007. "Alternative Control Methodologies for Patrolling Assets With Unmanned Air Vehicles," Lecture Notes in Economics and Mathematical Systems, in: Don Grundel & Robert Murphey & Panos Pardalos & Oleg Prokopyev (ed.), Cooperative Systems, pages 105-115, Springer.
    • Handle: RePEc:spr:lnechp:978-3-540-48271-0_7
    DOI: 10.1007/978-3-540-48271-0_7
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