Share Email Print

Proceedings Paper

Learned trafficability models
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper 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.

Paper Details

Date Published: 20 September 2001
PDF: 10 pages
Proc. SPIE 4364, Unmanned Ground Vehicle Technology III, (20 September 2001); doi: 10.1117/12.440008
Show Author Affiliations
Bruce Leonard Digney, Defence Research Establishment Suffield (Canada)

Published in SPIE Proceedings Vol. 4364:
Unmanned Ground Vehicle Technology III
Grant R. Gerhart; Chuck M. Shoemaker, Editor(s)

© SPIE. Terms of Use
Back to Top