Abstract
A fuzzy logic resource allocation algorithm that enables a collection of unmanned aerial vehicles (UAVs) to automatically cooperate will be discussed. The goal of the UAVs’ coordinated effort is to measure the atmospheric index of refraction. Once in flight no human intervention is required. A fuzzy logic based planning algorithm determines the optimal trajectory and points each UAV will sample, while taking into account the UAVs’ risk, risk tolerance, reliability, and mission priority for sampling in certain regions. It also considers fuel limitations, mission cost, and related uncertainties. The real-time fuzzy control algorithm running on each UAV renders the UAVs autonomous allowing them to change course immediately without consulting with any commander, requests other UAVs to help, and change the points that will be sampled when observing interesting phenomena. Simulations show the ability of the control algorithm to allow UAVs to effectively cooperate to increase the UAV team’s likelihood of success.
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Smith III, J.F., Nguyen, T.H. (2008). Fuzzy Logic Based UAV Allocation and Coordination. In: Cetto, J.A., Ferrier, JL., Costa dias Pereira, J., Filipe, J. (eds) Informatics in Control Automation and Robotics. Lecture Notes Electrical Engineering, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79142-3_8
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DOI: https://doi.org/10.1007/978-3-540-79142-3_8
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