The Area Processing Unit of Caroline - Finding the Way through DARPA’s Urban Challenge

  • Kai Berger
  • Christian Lipski
  • Christian Linz
  • Timo Stich
  • Marcus Magnor
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4931)

Abstract

This paper presents a vision-based color segmentation algorithm suitable for urban environments that separates an image into areas of drivable and non-drivable terrain. Assuming that a part of the image is known to be drivable terrain, other parts of the image are classified by comparing the Euclidean distance of each pixel’s color to the mean colors of the drivable area in real-time. Moving the search area depending on each frame’s result ensures temporal consistency and coherence. Furthermore, the algorithm classifies artifacts such as white and yellow lane markings and hard shadows as areas of unknown drivability. The algorithm was thoroughly tested on the autonomous vehicle ’Caroline’, which was a finalist in the 2007 DARPA Urban Challenge.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Kai Berger
    • 1
  • Christian Lipski
    • 1
  • Christian Linz
    • 1
  • Timo Stich
    • 1
  • Marcus Magnor
    • 1
  1. 1.Computer Graphics LabBraunschweigGermany

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