Feasible UAV path planning using genetic algorithms and Bézier curves

Authors:
Douglas Guimarães Macharet;Armando Alves Neto;Mario Fernando Montenegro Campos
Affiliations:
Computer Vision and Robotic Laboratory, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil;Computer Vision and Robotic Laboratory, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil;Computer Vision and Robotic Laboratory, Department of Computer Science, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
Venue:
SBIA'10 Proceedings of the 20th Brazilian conference on Advances in artificial intelligence
Year:
2010

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Abstract

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.