Appearance contrast for fast, robust trail-following

Authors:
Christopher Rasmussen;Yan Lu;Mehmet Kocamaz
Affiliations:
Dept. of Computer & Information Sciences, University of Delaware, Newark, DE;Dept. of Computer & Information Sciences, University of Delaware, Newark, DE;Dept. of Computer & Information Sciences, University of Delaware, Newark, DE
Venue:
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Year:
2009

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Abstract

We describe a framework for finding and tracking "trails" for autonomous outdoor robot navigation. Through a combination of visual cues and ladar-derived structural information, the algorithm is able to follow paths which pass through multiple zones of terrain smoothness, border vegetation, tread material, and illumination conditions. Our shape-based visual trail tracker assumes that the approaching trail region is approximately triangular under perspective. It generates region hypotheses from a learned distribution of expected trail width and curvature variation, and scores them using a robust measure of color and brightness contrast with flanking regions. The structural component analogously rewards hypotheses which correspond to empty or low-density regions in a groundstrike-filtered ladar obstacle map. Our system's performance is analyzed on several long sequences with diverse appearance and structural characteristics. Ground-truth segmentations are used to quantify performance where available, and several alternative algorithms are compared on the same data.