Vegetation Detection for Mobile Robot Navigation

David Bradley, Scott Thayer, Anthony (Tony) Stentz, and Peter Rander
tech. report CMU-RI-TR-04-12, Robotics Institute, Carnegie Mellon University, March, 2004


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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.

Keywords
Mobile Robot Perception, Outdoor Mobile Robotics, Vegetation Detection

Notes
Sponsor: DARPA
Grant ID: MDA972-01-9-0016
Associated Center(s) / Consortia: National Robotics Engineering Center
Associated Project(s): PerceptOR

Text Reference
David Bradley, Scott Thayer, Anthony (Tony) Stentz, and Peter Rander, "Vegetation Detection for Mobile Robot Navigation," tech. report CMU-RI-TR-04-12, Robotics Institute, Carnegie Mellon University, March, 2004

BibTeX Reference
@techreport{Bradley_2004_5287,
   author = "David Bradley and Scott Thayer and Anthony (Tony) Stentz and Peter Rander",
   title = "Vegetation Detection for Mobile Robot Navigation",
   booktitle = "",
   institution = "Robotics Institute",
   month = "March",
   year = "2004",
   number= "CMU-RI-TR-04-12",
   address= "Pittsburgh, PA",
}