This thesis addresses the problem of SLAM: simultaneous localization and mapping by robots in a dynamic environment. A multimodal approach using single-camera images and ultrasone range detectors on Pioneer-II robots is used. Kohonen self-organized maps are used to learn salient landmarks in the environment. Using odometry, it could be shown that the essential layout of the landmarks in the 2D plane can be reconstructed approximately using principal-component analysis on the odometry-distance map between pairs of visual landmarks.
