VITS-A Vision System for Autonomous Land Vehicle Navigation

  • Authors:
  • Matthew A. Turk;David G. Morgenthaler;Keith D. Gremban;Martin Marra

  • Affiliations:
  • Massachusetts Institute of Technology, Cambridge;-;Carnegie-Mellon Univ., Pittsburgh, PA;Massachusetts Institute of Technology, Cambridge

  • Venue:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence - Special Issue on Industrial Machine Vision and Computer Vision Technology:8MPart
  • Year:
  • 1988

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Abstract

A description is given of VITS (for vision task sequencer), the vision system for the autonomous land vehicle (ALV) Alvin, addressing in particular the task of road-following. The ALV vision system builds symbolic descriptions of road and obstacle boundaries using both video and range sensors. The authors discuss various road segmentation methods for video-based road-following, along with approaches to boundary extraction and transformation of boundaries in the image plane into a vehicle-centered three-dimensional scene model.