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Using Genetic Algorithms for Tasking Teams of Raven UAVs

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Abstract

Control of multiple unmanned aerial vehicles is of importance given that so many have been deployed in the field. This work discusses how genetic algorithms (GA) have been applied to the cooperative tasking of the AeroVironment’s Raven unmanned aerial vehicle (UAV) engaged in an intelligence, reconnaissance, and surveillance (ISR) mission. Mission assumptions, development of the GA, the method used to test for convergence, and the outcome of preliminary testing are all discussed.

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Authors and Affiliations

  1. Mathematics, West Virginia University, Morgantown, WV, USA

    Marjorie Darrah, Edgar Fuller, Thilanka Munasinghe & Kristin Duling

  2. Mechanical and Aerospace Engineering, West Virginia University, Morgantown, WV, USA

    Mridul Gautam

  3. Army Research Laboratory, Adelphi, MD, USA

    Mitchell Wathen

Authors
  1. Marjorie Darrah
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  2. Edgar Fuller
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  3. Thilanka Munasinghe
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  4. Kristin Duling
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  5. Mridul Gautam
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  6. Mitchell Wathen
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Corresponding author

Correspondence to Marjorie Darrah.

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Darrah, M., Fuller, E., Munasinghe, T. et al. Using Genetic Algorithms for Tasking Teams of Raven UAVs. J Intell Robot Syst 70, 361–371 (2013). https://doi.org/10.1007/s10846-012-9696-3

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  • DOI: https://doi.org/10.1007/s10846-012-9696-3

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