• DocumentCode
    2438027
  • Title

    Demonstration of Self-Training Autonomous Neural Networks in Space Vehicle Docking Simulations

  • Author

    Patrick, M. Clinton ; Thaler, Stephen L. ; Stevenson-Chavis, Katherine

  • Author_Institution
    Marshall Space Flight Center, Huntsville
  • fYear
    2007
  • fDate
    3-10 March 2007
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Neural networks have been under examination for decades in many areas of research, with varying degrees of success and acceptance. Key goals of computer learning, rapid problem solution, and automatic adaptation have been elusive at best. This paper1,2 summarizes efforts at NASA´s Marshall Space Flight Center harnessing such technology to autonomous space vehicle docking for the purpose of evaluating applicability to future missions.
  • Keywords
    aerospace computing; aerospace simulation; neural nets; space vehicles; NASA Marshall Space Flight Center; automatic adaptation; autonomous space vehicle docking simulations; computer learning; self-training autonomous neural networks; Artificial neural networks; Engines; Laboratories; NASA; Neural networks; Orbital robotics; Space technology; Space vehicles; Synthetic aperture sonar; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aerospace Conference, 2007 IEEE
  • Conference_Location
    Big Sky, MT
  • ISSN
    1095-323X
  • Print_ISBN
    1-4244-0524-6
  • Electronic_ISBN
    1095-323X
  • Type

    conf

  • DOI
    10.1109/AERO.2007.352649
  • Filename
    4161527