Branching to Find Feasible Solutions in Unmanned Air Vehicle Mission Planning

  • Cristian Ramírez-Atencia
  • Gema Bello-Orgaz
  • Maria D. R-Moreno
  • David Camacho
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8669)


Mission Planning is a classical problem that has been traditionally studied in several cases from Robotics to Space missions. This kind of problems can be extremely difficult in real and dynamic scenarios. This paper provides a first analysis for mission planning to Unmanned Air Vehicles (UAVs), where sensors and other equipment of UAVs to perform a task are modelled based on Temporal Constraint Satisfaction Problems (TCSPs). In this model, a set of resources and temporal constraints are designed to represent the main characteristics (task time, fuel consumption, ...) of this kind of aircrafts. Using this simplified TCSP model, and a Branch and Bound (B&B) search algorithm, a set of feasible solutions will be found trying to minimize the fuel cost, flight time spent and the number of UAVs used in the mission. Finally, some experiments will be carried out to validate both the quality of the solutions found and the spent runtime to found them.


unmanned aircraft systems mission planning temporal constraint satisfaction problems branch and bound 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Cristian Ramírez-Atencia
    • 1
  • Gema Bello-Orgaz
    • 1
  • Maria D. R-Moreno
    • 2
  • David Camacho
    • 1
  1. 1.Departamento de Ingeniería InformáticaUniversidad Autónoma de MadridMadridSpain
  2. 2.Departamento de AutomáticaUniversidad de AlcaláMadridSpain

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