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Unmanned Aerial Vehicle Swarms: The Design and Evaluation of Command and Control Strategies using Agent-Based Modeling

Unmanned Aerial Vehicle Swarms: The Design and Evaluation of Command and Control Strategies using Agent-Based Modeling

Alexander G. Madey
Copyright: © 2013 |Volume: 5 |Issue: 3 |Pages: 13
ISSN: 1943-0744|EISSN: 1943-0752|EISBN13: 9781466633940|DOI: 10.4018/ijats.2013070101
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MLA

Madey, Alexander G. "Unmanned Aerial Vehicle Swarms: The Design and Evaluation of Command and Control Strategies using Agent-Based Modeling." IJATS vol.5, no.3 2013: pp.1-13. http://doi.org/10.4018/ijats.2013070101

APA

Madey, A. G. (2013). Unmanned Aerial Vehicle Swarms: The Design and Evaluation of Command and Control Strategies using Agent-Based Modeling. International Journal of Agent Technologies and Systems (IJATS), 5(3), 1-13. http://doi.org/10.4018/ijats.2013070101

Chicago

Madey, Alexander G. "Unmanned Aerial Vehicle Swarms: The Design and Evaluation of Command and Control Strategies using Agent-Based Modeling," International Journal of Agent Technologies and Systems (IJATS) 5, no.3: 1-13. http://doi.org/10.4018/ijats.2013070101

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Abstract

Unmanned aerial vehicles (UAVs) are being widely used for both military and civilian purposes. The advent of smaller, lighter, less expensive UAVs opens opportunities to deploy a large number of small, semi-autonomous UAVs in a cohesive group or “swarm”. Swarms offer numerous advantages over single UAVs, such as higher coverage, redundancy in numbers and reduced long-range bandwidth requirements. Engineering a swarm requires designing the swarming behavior and finding effective ways to control the behavior so that the swarm can be directed to complete its mission. This paper presents an approach to developing UAV swarming behaviors and command and control (C2) strategies to govern them. The agent-based modeling toolkit NetLogo is used to create two mission types: contaminant plume mapping and vessel tracking. Performance metrics are used to evaluate success as parameters are changed. This research demonstrates the potential usefulness of agent-based modeling in the engineering of UAV swarms.

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