This article describes a rigorous and complete framework for the simultaneo
us localization and map building problem for mobile robots: the symmetries
and perturbations map (SPmap), which is based on a general probabilistic re
presentation of uncertain geometric information. me present a complete expe
riment with a LabMate(TM) mobile robot navigating in a human-made indoor en
vironment and equipped with a rotating two-dimensional (2-D) laser rangefin
der. Experiments validate the appropriateness of our approach and provide a
real measurement of the precision of the algorithms.