Terrain-based sensor selection for autonomous trail following

Authors:
Christopher Rasmussen;Donald Scott
Affiliations:
Dept. Computer & Information Sciences, University of Delaware;Dept. Computer & Information Sciences, University of Delaware
Venue:
RobVis'08 Proceedings of the 2nd international conference on Robot vision
Year:
2008

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Abstract

We introduce the problem of autonomous trail following without waypoints and present a vision- and ladar-based system which keeps to continuous hiking and mountain biking trails of relatively low human difficulty. Using a RANSAC-based analysis of ladar scans, trail-bordering terrain is classified as belonging to one of several major types: flat terrain, which exhibits low height contrast between on- and off-trail regions; thickly-vegetated terrain, which has corridor-like structure; and forested terrain, which has sparse obstacles and generally lower visual contrast. An adaptive color segmentation method for flat trail terrain and a height-based corridor-following method for thick terrain are detailed. Results are given for a number of autonomous runs as well as analysis of logged data, and ongoing work on forested terrain is discussed.