Appearance-based concurrent map building and localization

In appearance-based robot localization the environment map does not represent geometrical features but consists of an appearance map, which is a collection of robot poses and corresponding sensor observations. In this paper, we describe a concurrent map-building and localization (CML) system based on a multi-hypotheses tracker that is able to build and refine autonomously the appearance map required for localization as the robot moves in the environment. The results included in this paper validate our approach.