Learned trafficability models

Bruce Leonard Digney

doi:10.1117/12.440008

20 September 2001 Learned trafficability models

Bruce Leonard Digney

Proceedings Volume 4364, Unmanned Ground Vehicle Technology III; (2001) https://doi.org/10.1117/12.440008
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

While clearly necessary, geometric information is not sufficient to insure successful navigation in outdoor environments. Many barriers to navigation cannot be represented in a three dimensional geometric model alone. Barriers such as soft ground, snow, mud, loose sand, compliant vegetation, debris hidden in vegetation and annoyances such as small ruts and washboard effects do not appear in geometric representations. The difficulty of offline specification and changing nature of terrain characteristics requires that solutions be capable of learning without prior information and able to adapt as environmental conditions change. This paper will discuss the ongoing and proposed work the Learned Trafficability Models (LTMs) program at the Defence Research Establishment Suffield (DRES) of the Canadian Department of National Defence.

Citation Download Citation

Bruce Leonard Digney "Learned trafficability models", Proc. SPIE 4364, Unmanned Ground Vehicle Technology III, (20 September 2001); https://doi.org/10.1117/12.440008

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