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Detection of Drivable Corridors for Off-Road Autonomous Navigation

12 years 11 months ago
Detection of Drivable Corridors for Off-Road Autonomous Navigation
This paper describes a hierarchical Bayesian network used for segmenting desert images and detecting off road drivable corridors for autonomous navigation. Unlike the embedded hidden Markov model the Bayesian network presented in this paper can successfully account for natural dependencies between neighboring pixels in both image dimensions making it more suitable for a larger class of images. The method described here was developed within the Stanford racing team that won the DARPA Grand Challenge 2005 after driving over 130 miles autonomously in the Nevada desert.
Ara V. Nefian, Gary R. Bradski
Added 22 Oct 2009
Updated 27 Oct 2009
Type Conference
Year 2006
Where ICIP
Authors Ara V. Nefian, Gary R. Bradski
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