Simultaneous localization and map construction method using omnidirectional stereoscopic information

This paper deals with the localization and map building paradigm in an unknown indoor environment. We propose an exploration method based on the use of the sensorial data provided by an omnidirectional stereoscopic vision system. First, we link the problem of sensorial model construction with two omnidirectional images. We propose an approach based on the fusion of several criteria, which is realized according to Dempster-Shafer rules. We then deal with the matching problem of the stereo sensorial model with an environment map integrating all the previous primitive observations. We propose two matching approaches based on different selection criteria: the Hausdorff distance and the cumulated Cartesian distance. We also present our incremental map building paradigm based on the hypothesis of a non a priori knowledge. Finally, we deal with the problem of allowing a robot to localize itself and to construct concurrently a representation of its environment.