This paper deals with self-localization of a mobile robot on the condition that no a-priori knowledge about the environment is available. The applied method features accurate, robust, independent of any artificial lan...
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This paper deals with self-localization of a mobile robot on the condition that no a-priori knowledge about the environment is available. The applied method features accurate, robust, independent of any artificial landmarks and feasible with such a moderate computational effort that all necessary tasks can be executed in real-time on a standard PC. The perception system used is a panorama laser range finder which takes scans of its present environment. A modified dynamic programming.algorithm provides pattern matching.and pattern recognition on the preprocessed panorama scans and thereby renders a qualitative fusion of the sensory data. For an exactly quantitative estimate of the robot's current position, a robust localization module is employed. The knowledge gained on the environment is stored in a self-growing. graph based map which combines geometrical information and topological restrictions. Preliminary experiments in an ordinary office environment proved the reliability and efficiency of the system.
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