| Abstract: |  This thesis presents simultaneous localization and mapping algorithm for a small mobile robot. The designed solution enables to determine a mobile robot's and landmark positions using self-localization and camera based landmark detection. As landmarks, roundel patterns are used that are positioned statically on obstacles or borders of the used arena. One of the key features is the suppression of odometry error in long term use of robot. As hardware platform, modular robots were used from the Replicator and Symbrion project, both funded by the European Commission. Proposed method uses the extended Kalman filter for merging data from odometry and camera landmark detection for building landmark-based map.
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