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Alvinn: An Autonomous Land Vehicle in a Neural Network.


ADA218975

Publication Date 1989
Personal Author Pomerleau, D. A.
Page Count 17
Abstract ALVINN (Autonomous Land Vehicle In a Neural Network) is a 3-layer back-propagation network designed for the task of road following. Currently ALVINN takes images from a camera and a laser range finder as input and produces as output the direction the vehicle should travel in order to follow the road. Training has been conducted using simulated road images. Successful tests on the Carnegie Mellon autonomous navigation test vehicle indicate that the network can effectively follow real roads under certain field conditions. The representation developed to perform the task differs dramatically when the network is trained under various conditions, suggesting the possibility of a novel adaptive autonomous navigation system capable of tailoring its processing to the conditions at hand. Keywords: Autonomous navigation, Neural networks, Road following, Machine vision. (sdw)
Keywords
  • Autonomous navigation
  • Ground vehicles
  • Neural nets
  • Adaptive systems
  • Field conditions
  • Images
  • Laser applications
  • Processing
  • Range finding
  • Roads
  • Simulation
  • Test vehicles
  • Autonomous land vehicles
  • Computer vision
Source Agency
  • Non Paid ADAS
  • NSF General
NTIS Subject Category
  • 85H - Road Transportation
  • 76D - Navigation Systems
  • 62 - Computers, Control & Information Theory
Corporate Authors Carnegie-Mellon Univ., Pittsburgh, PA. Artificial Intelligence and Psychology Project.
Supplemental Notes Sponsored in part by Contracts N00014-87-K-0385, N00014-87-K-0533, N00039-87-C-0251, DACA76-85-C-0003 and Grants NSF-EET87-16324.
Document Type Technical Report
Title Note Technical rept.
NTIS Issue Number 199013
Contract Number
  • N00014-86-K-0678
Alvinn: An Autonomous Land Vehicle in a Neural Network.
Alvinn: An Autonomous Land Vehicle in a Neural Network.
ADA218975

  • Autonomous navigation
  • Ground vehicles
  • Neural nets
  • Adaptive systems
  • Field conditions
  • Images
  • Laser applications
  • Processing
  • Range finding
  • Roads
  • Simulation
  • Test vehicles
  • Autonomous land vehicles
  • Computer vision
  • Non Paid ADAS
  • NSF General
  • 85H - Road Transportation
  • 76D - Navigation Systems
  • 62 - Computers, Control & Information Theory
  • N00014-86-K-0678
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