This paper presents an approach to vision-based mobile robot
localization. In an attempt to capitalize on the benefits of both
image and landmark-based methods, we describe a method that combines
their strengths. Images are encoded as a set of visual features
called landmarks. Potential landmarks are detected using an
attention mechanism implemented as a measure of uniqueness. They are
then selected and represented by an appearance-based encoding.
Localization is performed using a landmark tracking and
interpolation method which obtains an estimate accurate to a
fraction of the environment sampling density. Experimental results
are shown to confirm the feasibility and accuracy of the method.