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Robust UAV Mission Planning

Author

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  • Evers, L.
  • Dollevoet, T.A.B.
  • Barros, A.I.
  • Monsuur, H.

Abstract

Unmanned Areal Vehicles (UAVs) can provide significant contributions to information gathering in military missions. UAVs can be used to capture both full motion video and still imagery of specific target locations within the area of interest. In order to improve the effectiveness of a reconnaissance mission, it is important to visit the largest number of interesting target locations possible, taking into consideration operational constraints related to fuel usage between target locations, weather conditions and endurance of the UAV. We model this planning problem as the well-known orienteering problem, which is a generalization of the traveling salesman problem. Given the uncertainty in the military operational environment, robust planning solutions are required. As such, our model takes into account uncertainty in the fuel usage between targets (for instance due to weather conditions) as well as uncertainty in the importance of visiting specific target locations. We report results using different uncertainty sets that specify the degree of uncertainty against which any feasible solution will be protected. We also compare the probability that a solution is feasible for the robust solution on one hand and the solution found with average fuel usage and expected value of information on the other. In doing so, we show how the sustainability of a UAV mission can be significantly improved.

Suggested Citation

  • Evers, L. & Dollevoet, T.A.B. & Barros, A.I. & Monsuur, H., 2011. "Robust UAV Mission Planning," Econometric Institute Research Papers EI 2011-07, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:22802
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    References listed on IDEAS

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    1. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
    2. Matteo Fischetti & Juan José Salazar González & Paolo Toth, 1998. "Solving the Orienteering Problem through Branch-and-Cut," INFORMS Journal on Computing, INFORMS, vol. 10(2), pages 133-148, May.
    3. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
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    Cited by:

    1. Aharon Ben-Tal & Ruud Brekelmans & Dick den Hertog & Jean-Philippe Vial, 2017. "Globalized Robust Optimization for Nonlinear Uncertain Inequalities," INFORMS Journal on Computing, INFORMS, vol. 29(2), pages 350-366, May.
    2. Evers, L. & Glorie, K.M. & van der Ster, S. & Barros, A.I. & Monsuur, H., 2012. "The Orienteering Problem under Uncertainty Stochastic Programming and Robust Optimization compared," Econometric Institute Research Papers EI 2012-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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