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In Proc. of Intl. Symp. on Experimental Robotics (ISER) Rio de Janeiro, Brazil, July 2006

Summary: In Proc. of Intl. Symp. on Experimental Robotics (ISER)
Rio de Janeiro, Brazil, July 2006
Outdoor Mapping and Navigation using Stereo Vision
Kurt Konolige, Motilal Agrawal, Robert C. Bolles, Cregg Cowan, Martin Fischler,
and Brian Gerkey
Artificial Intelligence Center, SRI International, Menlo Park, CA 94025
1 Introduction
We consider the problem of autonomous navigation in an unstructured outdoor envi-
ronment. The goal is for a small outdoor robot to come into a new area, learn about
and map its environment, and move to a given goal at modest speeds (1 m/s). This
problem is especially difficult in outdoor, off-road environments, where tall grass,
shadows, deadfall, and other obstacles predominate. Not surprisingly, the biggest
challenge is acquiring and using a reliable map of the new area. Although work
in outdoor navigation has preferentially used laser rangefinders [13, 2, 6], we use
stereo vision as the main sensor. Vision sensors allow us to use more distant objects
as landmarks for navigation, and to learn and use color and texture models of the
environment, in looking further ahead than is possible with range sensors alone.
In this paper we show how to build a consistent, globally correct map in real
time, using a combination of the following vision-based techniques:
Efficient, precise stereo algorithms. We can perform stereo analysis on 512x384


Source: Agrawal, Motilal - Artificial Intelligence Center, SRI International


Collections: Computer Technologies and Information Sciences