• DocumentCode
    2474529
  • Title

    An experimental validation of reinforcement learning applied to the position control of UAVs

  • Author

    Santos, Sérgio Ronaldo Barros dos ; Givigi, Sidney N., Jr. ; Júnior, Cairo Lúcio Nascimento

  • Author_Institution
    Div. of Electron. Eng., Inst. Tecnol. de Aeronaut., São José dos Campos, Brazil
  • fYear
    2012
  • fDate
    14-17 Oct. 2012
  • Firstpage
    2796
  • Lastpage
    2802
  • Abstract
    In this paper, we explore the application of Reinforcement Learning (RL) to the derivation of control laws for the flight control of an unmanned aerial vehicle (UAV). The controllers are derived off-line with a simulation and the solutions are ported to an actual aircraft. Experimental results showed that the controllers stabilize the quad-rotor during the path tracking as has been learned in the simulation.
  • Keywords
    aircraft control; autonomous aerial vehicles; learning systems; position control; RL; UAV; aircraft; flight control; path tracking; position control; quad-rotor; reinforcement learning; unmanned aerial vehicle; Aerodynamics; Atmospheric modeling; Attitude control; Computational modeling; Learning; Learning automata; Vectors; Reinforcement Learning; Unmanned Air Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4673-1713-9
  • Electronic_ISBN
    978-1-4673-1712-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2012.6378172
  • Filename
    6378172