Simultaneous map building and localization for mobile robots: a multisensor fusion approach

During mobile robot navigation, position estimates obtained by odometry drift with time, therefore becoming unrealistic and useless. This work enhances the use of external mechanisms by considering a multisensor system, composed of a 2D laser rangefinder and an off-the-shelf CCD camera, which provides redundancy and assures reliability and precision of the observed features. We simultaneously consider both the map building and the localization problems using a state vector approach, which is related to the location estimations of both the robot and the map features, whilst its covariance matrix reflects the relationships between them. Relevance and importance of its off-diagonal elements is demonstrated by their contributions to “backwards estimations” whenever the vehicle returns to places in the navigation area which have been already visited and learned. Real experiments are presented, considering a LabMate mobile robot navigating in an static indoor environment