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Proceedings Paper

Learned trafficability for UGVs: inferring geometry from imagery
Author(s): Gregory S. Broten; David Mackay; Bruce Digney
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Paper Abstract

Unmanned ground vehicles (UGV) operating in outdoor environments must traverse unstructured terrain. This terrain is diverse in nature and contains natural obstacles such as rocks, brushes, berms, and low lying wet areas. Outdoor terrain is not static as it varies on a seasonal basis due to the life cycle associated with natural vegetation. Additionally, outdoor terrain may change appearance due to variations in lighting conditions that result from the Sun's relative position and from weather conditions such as clouds, fog or rain. This environmental diversity has long caused researchers considerable grief, as developing a classical terrain classification algorithm has proven to be a very difficult if not an impossible task. Researchers have skirted this problem by relying upon ranging sensors and constructing 2 ½D or, more recently, 3D world representations. Although geometrical representations have been used extensively, the low data rates associated with laser rangefinders, the unreliability of stereo vision, and the interaction between geometry and orientation estimation errors have limited the lookahead distance, thereby reducing the maximum attainable vehicle speeds. Learning from experience, in a more human like manner, promises to reduce or alleviate many of the issues posed by unstructured outdoor terrain. Defence R&D Canada (DRDC) "Learned Trafficability" program researches learning from experience. The paper presents DRDC's progress in extending a 2 ½D world representation using vision and learning from experience.

Paper Details

Date Published: 16 April 2008
PDF: 12 pages
Proc. SPIE 6962, Unmanned Systems Technology X, 69620F (16 April 2008); doi: 10.1117/12.776716
Show Author Affiliations
Gregory S. Broten, Defence Research and Development Canada (Canada)
David Mackay, Defence Research and Development Canada (Canada)
Bruce Digney, Defence Research and Development Canada (Canada)


Published in SPIE Proceedings Vol. 6962:
Unmanned Systems Technology X
Grant R. Gerhart; Douglas W. Gage; Charles M. Shoemaker, Editor(s)

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