Branching to find feasible solutions in unmanned air vehicle mission planning
Entidad
UAM. Departamento de Ingeniería InformáticaEditor
Springer Berlin HeidelbergFecha de edición
2014Cita
10.1007/978-3-319-10840-7_35
Intelligent Data Engineering and Automated Learning – IDEAL 2014: 15th International Conference, Salamanca, Spain, September 10-12, 2014. Proceedings. Lecture Notes in Computer Science, Volumen 8669. Springer, 2014. 286-294.
ISSN
0302-9743 (print); 1611-3349 (online)ISBN
978-3-319-10839-1 (print); 978-3-319-10840-7 (online)DOI
10.1007/978-3-319-10840-7_35Financiado por
This work is supported by the Spanish Ministry of Science and Education under Project Code TIN2010-19872 and Savier Project (Airbus Defence & Space, FUAM-076915).Versión del editor
http://dx.doi.org/10.1007/978-3-319-10840-7_35Materias
Unmanned aircraft systems; Mission planning; Temporal constraint satisfaction problems; Branch and bound; InformáticaNota
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-10840-7_35Proceedings 15th International Conference, Salamanca, Spain, September 10-12, 2014.
Derechos
© Springer-Verlag Berlin Heidelberg 2014Resumen
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.
Lista de ficheros
Google Scholar:Ramírez Atencia, Cristian Oliver
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Bello Orgaz, Gema
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R-Moreno, María Dolores
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Camacho, David
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