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IROS
2009
IEEE

Improving robot navigation in structured outdoor environments by identifying vegetation from laser data

8 years 12 months ago
Improving robot navigation in structured outdoor environments by identifying vegetation from laser data
— This paper addresses the problem of vegetation detection from laser measurements. The ability to detect vegetation is important for robots operating outdoors, since it enables a robot to navigate more efficiently and safely in such environments. In this paper, we propose a novel approach for detecting low, grass-like vegetation using laser remission values. In our algorithm, the laser remission is modeled as a function of distance, incidence angle, and material. We classify surface terrain based on 3D scans of the surroundings of the robot. The model is learned in a self-supervised way using vibrationbased terrain classification. In all real world experiments we carried out, our approach yields a classification accuracy of over 99%. We furthermore illustrate how the learned classifier can improve the autonomous navigation capabilities of mobile robots.
Kai M. Wurm, Rainer Kümmerle, Cyrill Stachnis
Added 24 May 2010
Updated 24 May 2010
Type Conference
Year 2009
Where IROS
Authors Kai M. Wurm, Rainer Kümmerle, Cyrill Stachniss, Wolfram Burgard
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