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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Feasible UAV Path Planning Using Genetic Algorithms and Bézier Curves
verfasst von : Douglas Guimarães Macharet, Armando Alves Neto, Mario Fernando Montenegro Campos
Erschienen in: Advances in Artificial Intelligence – SBIA 2010
Verlag: Springer Berlin Heidelberg
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With the growing in the use of UAVs (Unmanned Aerial Vehicles), it is necessary to develop techniques that allow the generation of feasible paths for these vehicles. These paths take into account the nonholonomic constraints intrinsic to UAVs, such as minimum curvature, minimum torsion and maximum climb (or dive) angle. Thus, this paper proposes the use of genetic algorithms to generate paths for these vehicles in the three-dimensional space, using Bézier curves with several advantages. We consider all these three constraints in order to generate a feasible path for a small fixed-wing aircraft with severe limitations. We show results for this vehicle.