Vegetation Detection for Mobile Robot Navigation
Tech. Report, CMU-RI-TR-04-12, Robotics Institute, Carnegie Mellon University, February, 2004
Abstract
Described is the development and testing of a robust vegetation detector for mobile robot navigation. A multispectral sensor was created out of a near-infrared and a visible light video camera. Vegetation was then detected by subtracting each pixel in the red channel of the visible-light image from the corresponding pixel in the near-infrared image and thresholding the result. This computationally-efficient technique has been verified to be a robust chlorophyll detector in natural environments.
BibTeX
@techreport{Bradley-2004-8857,author = {David Bradley and Scott Thayer and Anthony (Tony) Stentz and Peter Rander},
title = {Vegetation Detection for Mobile Robot Navigation},
year = {2004},
month = {February},
institute = {Carnegie Mellon University},
address = {Pittsburgh, PA},
number = {CMU-RI-TR-04-12},
keywords = {Mobile Robot Perception, Outdoor Mobile Robotics, Vegetation Detection},
}
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