Perception for learned trafficability models

Gregory S. Broten; Bruce Leonard Digney

doi:10.1117/12.474446

17 July 2002 Perception for learned trafficability models

Proceedings Volume 4715, Unmanned Ground Vehicle Technology IV; (2002) https://doi.org/10.1117/12.474446
Event: AeroSense 2002, 2002, Orlando, FL, United States

Abstract

Unmanned ground vehicles (UGV), traversing open terrain, require the capability of identifying non-geometric barriers or impediments to navigation, such as soft soil, fine sand, mud, snow, compliant vegetation, washboard, and ruts. Given the ever changing nature of these terrain characteristics, for an UVG to be able to consistently navigate such barriers, it must have the ability to learn from and to adapt to changes in these environmental conditions. As part of ongoing research co-operation with the Defense Research Establishment Suffield (DRES), Scientific Instrumentation Ltd. (SIL) has developed a Terrain Simulator that allows for the investigation of terrain perception and of learning techniques.

Citation Download Citation

Gregory S. Broten and Bruce Leonard Digney "Perception for learned trafficability models", Proc. SPIE 4715, Unmanned Ground Vehicle Technology IV, (17 July 2002); https://doi.org/10.1117/12.474446

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