Abstract
The study of Unmanned Aerial Vehicles (UAVs) is currently a growing area. The accelerated expansion of these technologies is demanding the work of more and more qualified operators, able to supervise and control multiple UAVs at the same time. Unfortunately, the training process for this type of systems is still unstructured, and it is needed to define methods to assess and classify operators in the context of a specific skill, for both novice users and experts. This work is focused on analyzing the planning and monitoring skills of inexperienced users in a multi-UAV simulation environment, through the use of a set of metrics capturing the performance of a user and defining its profile. The user profiles will be clustered to extract shared behavioral patterns that help us to decide the planning and monitoring level for each group of users, and to select potential operators.
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Acknowledgments
This work is supported by the Spanish Ministry of Science and Education under Project Code TIN2014-56494-C4-4-P, Comunidad Autonoma de Madrid under project CIBERDINE S2013/ICE-3095, and Savier an Airbus Defense & Space project (FUAM-076914 and FUAM-076915). The authors would like to acknowledge the support obtained from Airbus Defence&Space, specially from Savier Open Innovation project members: José Insenser, Gemma Blasco, Juan Antonio Henríquez and César Castro.
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Rodríguez-Fernández, V., Menéndez, H.D., Camacho, D. (2015). Analyzing Planning and Monitoring Skills of Users in a Multi-UAV Simulation Environment. In: Puerta, J., et al. Advances in Artificial Intelligence. CAEPIA 2015. Lecture Notes in Computer Science(), vol 9422. Springer, Cham. https://doi.org/10.1007/978-3-319-24598-0_23
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DOI: https://doi.org/10.1007/978-3-319-24598-0_23
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