• DocumentCode
    2698598
  • Title

    Path planning based on Genetic Algorithms and the Monte-Carlo method to avoid aerial vehicle collisions under uncertainties

  • Author

    Cobano, J.A. ; Conde, R. ; Alejo, D. ; Ollero, A.

  • Author_Institution
    Univ. of Seville, Seville, Spain
  • fYear
    2011
  • fDate
    9-13 May 2011
  • Firstpage
    4429
  • Lastpage
    4434
  • Abstract
    This paper presents a collision-free path planning method for an aerial vehicle sharing airspace with other aerial vehicles. It is based on grid models and genetic algorithms to find safe trajectories. Monte-Carlo method is used to evaluate the best predicted trajectories considering different sources of uncertainty such as the wind, the inaccuracies in the vehicle model and limitations of on-board sensors and control system.
  • Keywords
    Monte Carlo methods; aircraft control; collision avoidance; genetic algorithms; sensors; Monte Carlo method; aerial vehicle collision; collision-free path planning; genetic algorithm; grid model; on-board sensor; Atmospheric modeling; Computational modeling; Genetic algorithms; Prediction algorithms; Trajectory; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation (ICRA), 2011 IEEE International Conference on
  • Conference_Location
    Shanghai
  • ISSN
    1050-4729
  • Print_ISBN
    978-1-61284-386-5
  • Type

    conf

  • DOI
    10.1109/ICRA.2011.5980246
  • Filename
    5980246
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2698598