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.
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Rasmussen, C., Scott, D. (2008). Terrain-Based Sensor Selection for Autonomous Trail Following. In: Sommer, G., Klette, R. (eds) Robot Vision. RobVis 2008. Lecture Notes in Computer Science, vol 4931. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78157-8_26
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DOI: https://doi.org/10.1007/978-3-540-78157-8_26
Publisher Name: Springer, Berlin, Heidelberg
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