• DocumentCode
    3228371
  • Title

    Autonomous helicopter hover using an artificial neural network

  • Author

    Buskey, Gregg ; Wyeth, Gordon ; Roberts, Jonathan

  • Author_Institution
    Comput. Sci. & Electr. Eng., Queensland Univ., St. Lucia, Qld., Australia
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1635
  • Abstract
    Details the developments to date of an unmanned air vehicle (UAV) based on a standard size 60 model helicopter. The design goal is to have the helicopter achieve stable hover with the aid of an INS and stereo vision. The focus of the paper is on the development of an artificial neural network (ANN) that makes use of only the INS data to generate hover commands, which are used to directly manipulate the flight servos. Current results show that networks incorporating some form of recurrency (state history) offer little advantage over those without. At this stage, the ANN has partially maintained periods of hover even with misaligned sensors.
  • Keywords
    aircraft control; helicopters; inertial navigation; neurocontrollers; recurrent neural nets; remotely operated vehicles; stereo image processing; INS; autonomous helicopter hover; flight servos; hover commands; stereo vision; unmanned air vehicle; Actuators; Aerodynamics; Artificial neural networks; Australia; Control systems; Helicopters; Servomechanisms; Stereo vision; Unmanned aerial vehicles; Vehicle dynamics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 2001. Proceedings 2001 ICRA. IEEE International Conference on
  • ISSN
    1050-4729
  • Print_ISBN
    0-7803-6576-3
  • Type

    conf

  • DOI
    10.1109/ROBOT.2001.932845
  • Filename
    932845