2010 | OriginalPaper | Chapter
Feasible UAV Path Planning Using Genetic Algorithms and Bézier Curves
Authors : Douglas Guimarães Macharet, Armando Alves Neto, Mario Fernando Montenegro Campos
Published in: Advances in Artificial Intelligence – SBIA 2010
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
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.