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Proceedings Paper

Ladar-based terrain cover classification
Author(s): Jose Macedo; Roberto Manduchi; Larry Henry Matthies
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Paper Abstract

An autonomous vehicle driving in a densely vegetated environment needs to be able to discriminate between obstacles (such as rocks) and penetrable vegetation (such as tall grass). We propose a technique for terrain cover classification based on the statistical analysis of the range data produced by a single-axis laser rangefinder (ladar). We first present theoretical models for the range distribution in the presence of homogeneously distributed grass and of obstacles partially occluded by grass. We then validate our results with real-world cases, and propose a simple algorithm to robustly discriminate between vegetation and obstacles based on the local statistical analysis of the range data.

Paper Details

Date Published: 20 September 2001
PDF: 7 pages
Proc. SPIE 4364, Unmanned Ground Vehicle Technology III, (20 September 2001); doi: 10.1117/12.439986
Show Author Affiliations
Jose Macedo, Univ. of San Diego (United States)
Roberto Manduchi, Jet Propulsion Lab. (United States)
Larry Henry Matthies, Jet Propulsion Lab. (United States)

Published in SPIE Proceedings Vol. 4364:
Unmanned Ground Vehicle Technology III
Grant R. Gerhart; Chuck M. Shoemaker, Editor(s)

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