• DocumentCode
    957655
  • Title

    A simplified neural network solution through problem decomposition: the case of the truck backer-upper

  • Author

    Jenkins, Robert E. ; Yuhas, Ben P.

  • Author_Institution
    Appl. Phys. Lab., Johns Hopkins Univ., Baltimore, MD, USA
  • Volume
    4
  • Issue
    4
  • fYear
    1993
  • fDate
    7/1/1993 12:00:00 AM
  • Firstpage
    718
  • Lastpage
    720
  • Abstract
    D.H. Nguyen and B. Widrow (1990) demonstrated that a feedforward neural network can be trained to steer a tractor-trailer truck to a dock while backing up. The feedforward network they used to control the truck contained 25 hidden units and required extensive training. The authors demonstrate that a very simple solution to the truck backer-upper exists and can be found by decomposing the problem into subtasks. By hard-wiring these control laws into a network, they found a controller with only two hidden units that performs as well as the larger controller trained from scratch. This approach could be used to build up more complex controllers from simple components
  • Keywords
    feedforward neural nets; learning (artificial intelligence); position control; road vehicles; feedforward neural network; hidden units; problem decomposition; steering control; tractor-trailer truck; Computer aided software engineering; Error correction; Feedforward neural networks; Feedforward systems; Goniometers; Laboratories; Neural networks; Nonlinear control systems; Physics; Wheels;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/72.238326
  • Filename
    238326