• DocumentCode
    2655651
  • Title

    Goal directed model inversion

  • Author

    Colombano, Silvano P. ; Compton, Michael ; Bualat, Maria

  • Author_Institution
    NASA-Ames Res. Center, Moffett Field, CA, USA
  • fYear
    1991
  • fDate
    18-21 Nov 1991
  • Firstpage
    2422
  • Abstract
    A new neural network technique for model inversion called goal directed model inversion (GDM) is presented. It allows the system to produce an inverse model in a goal directed manner. The major advantage of an inverse model created in this matter is that it can adapt to unexpected changes in the system with which it must interact. As an example of the GDMI technique, a simple kinematic controller was built for a simulated robotic arm with three degrees of freedom. The system was trained by presenting a sequence of goals of increasing difficulty in some required region of space. As the controller was trained, its ability to extrapolate correct control actions to new distant goals increased
  • Keywords
    controllers; kinematics; learning systems; neural nets; robots; goal directed model inversion; kinematic controller; neural network technique; simulated robotic arm; training; unexpected changes; Bridges; Error correction; Inverse problems; Neural networks; Orbital robotics; Position measurement; Robot kinematics; Sampling methods; Supervised learning; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1991. 1991 IEEE International Joint Conference on
  • Print_ISBN
    0-7803-0227-3
  • Type

    conf

  • DOI
    10.1109/IJCNN.1991.170751
  • Filename
    170751