Fast Recognition of Self-Similar Landmarks
Daniel Scharstein
Amy J. Briggs
Abstract
Mobile robot localization and navigation require robust and
efficient methods for utilizing perceptual information. In this
paper we propose a design for simple visual landmarks that can be
unobtrusively added to an environment for navigation without a
global geometric map of the workspace. We describe self-similar
intensity patterns together with an efficient and reliable algorithm
for their detection that can handle a wide range of affine
transformations.
A gzip'ed postscript version
of this paper is available.
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