This article describes a rigorous and complete framework for the simultaneous localization and map building problem for mobile robots: the symmetries and perturbation map (SPmap), which is based on a general probabilistic representation of uncertain geometric information. We present a complete experiment with a LabMate/sup TM/ mobile robot navigating in a human-made indoor environment and equipped with a rotating 2D laser rangefinder. Experiments validate the appropriateness of our approach and provide a real measurement of the precision of the algorithms.
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