Robust and Agile UAV Mission Planning

L (Lanah) Evers

Research output: Types of ThesisDoctoral ThesisExternally prepared

Abstract

Unmanned Aerial 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, 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. Therefore, our model takes into account uncertainty in the fuel usage between targets, for instance due to weather conditions. We report results for 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 solutions on one hand and the solution found with average fuel usage on the other. These probabilities are assessed both by simulation and by derivation of problem specific theoretical bounds on the probability of constraint feasibility. In doing so, we show how the sustainability of a UAV mission can be significantly improved. Additionally, we suggest how the robust solution can be operationalized in a realistic setting, by complementing the robust tour with agility principles.
Original languageEnglish
Awarding Institution
  • Erasmus University Rotterdam
Supervisors/Advisors
  • Wagelmans, Albert, Supervisor
  • Barros, AI, Supervisor, External person
  • Monsuur, H, Supervisor, External person
Award date28 Nov 2013
Place of PublicationRotterdam
Print ISBNs9783319120751
Publication statusPublished - 28 Nov 2013

Research programs

  • EUR ESE 31

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