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

Kai M. Wurm, Rainer Kummerle, Cyrill Stachniss, Wolfram Burgard
2009 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems  
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
more » ... 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.
doi:10.1109/iros.2009.5354530 dblp:conf/iros/WurmKSB09 fatcat:i2d7y46nhbc7jfqme4e5ykfbja