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Feasible UAV Path Planning Using Genetic Algorithms and Bézier Curves

  • Douglas Guimarães Macharet
  • Armando Alves Neto
  • Mario Fernando Montenegro Campos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6404)

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.

Keywords

Path planning UAVs Bézier curves Genetic algorithm 

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References

  1. 1.
    Siegwart, R., Nourbakhsh, I.R.: Introduction to Autonomous Mobile Robots. MIT Press, Cambridge (2004)Google Scholar
  2. 2.
    LaValle, S.M.: Planning Algorithms. Cambridge University Press, Cambridge (2006)CrossRefzbMATHGoogle Scholar
  3. 3.
    Dubins, L.E.: On Curves of Minimal Length with a Constraint on Average Curvature, and with Prescribed Initial and Terminal Positions and Tangents. American Journal of Mathematics 79, 497–516 (1957)MathSciNetCrossRefzbMATHGoogle Scholar
  4. 4.
    Kuwata, Y., Richards, A., Schouwenaars, T., How, J.P.: Robust Constrained Receding Horizon Control for Trajectory Planning. In: Proceedings of the AIAA Guidance, Navigation and Control Conference (2005)Google Scholar
  5. 5.
    Wzorek, M., Doherty, P.: Reconfigurable Path Planning for an Autonomous Unmanned Aerial Vehicle. In: International Conference on Hybrid Information Technology, ICHIT 2006, pp. 242–249 (November 2006)Google Scholar
  6. 6.
    Bortofi, S.A.: Path Planning for UAVs. In: Proceedings of the American Control Conference (2000)Google Scholar
  7. 7.
    Dogan, A.: Probabilistic Path Planning for UAVs. In: Proceedings of 2nd AIAA Unmanned Unlimited Systems, Technologies, and Operations (2003)Google Scholar
  8. 8.
    Cheng, P., Shen, Z., Lavalle, S.M.: RRT-Based Trajectory Design for Autonomous Automobiles and Spacecraft. Archives of Control Sciences 11(3-4), 167–194 (2001)MathSciNetzbMATHGoogle Scholar
  9. 9.
    Nikolos, I., Valavanis, K., Tsourveloudis, N., Kostaras, A.: Evolutionary algorithm based offine/online path planner for UAV navigation. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 33(6), 898–912 (2003)CrossRefGoogle Scholar
  10. 10.
    Hasircioglu, I., Topcuoglu, H.R., Ermis, M.: 3-d path planning for the navigation of unmanned aerial vehicles by using evolutionary algorithms. In: GECCO 2008: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation, pp. 1499–1506. ACM, New York (2008)Google Scholar
  11. 11.
    de la Cruz, J.M., Besada-Portas, E., Torre-Cubillo, L., Andres-Toro, B., Lopez- Orozco, J.A.: Evolutionary path planner for uavs in realistic environments. In: GECCO 2008: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation, pp. 14–77. ACM, New York (2008)Google Scholar
  12. 12.
    Pehlivanoglu, Y.V., Baysal, O., Hacioglu, A.: Path planning for autonomous UAV via vibrational genetic algorithm. Aircraft Engineering and Aerospace Technology: An International Journal 79(8), 352–359 (2007)CrossRefGoogle Scholar
  13. 13.
    Kreyszig, E.: Differential Geometry, vol. 1. Dover Publications, New York (1991)zbMATHGoogle Scholar
  14. 14.
    Farouki, R.T., Han, C.Y.: Algorithms for Spatial Pythagorean-Hodograph Curves. In: Geometric Properties for Incomplete Data, pp. 43–58 (2006)Google Scholar
  15. 15.
    Farouki, R.T.: The Elastic Bending Energy of Pythagorean Hodograph Curves. Comput. Aided Geom. Design 13, 227–241 (1996)MathSciNetCrossRefzbMATHGoogle Scholar
  16. 16.
    Alves Neto, A., Campos, M.F.M.: On the generation of feasible paths for aerial robots with limited climb angle. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2009), Kobe, Japan (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Douglas Guimarães Macharet
    • 1
  • Armando Alves Neto
    • 1
  • Mario Fernando Montenegro Campos
    • 1
  1. 1.Computer Vision and Robotic Laboratory (VeRLab), Department of Computer ScienceUniversidade Federal de Minas GeraisBelo HorizonteBrazil

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