Abstract
The paper presents an approach for localizing a mobile robot in a feature-based map using a 2D laser rangefinder and wheel odometry. As the presented approach is based on set membership methods, the localization result consists of sets instead of points, and is guaranteed to contain the true robot position as long as the sensor errors are absolutely bounded and a maximum number of measurement outliers can be assumed. It is able to cope with a multitude of measurement per time step compared to previous approaches. Moreover, the approach is capable of identifying and marking outlier points in the laser range scan. A real world experiment, where a mobile robot is moving in a structured indoor environment with previously unmapped static and dynamic obstacles shows the feasibility of the approach. It is shown that the true robot pose is always included in the solution set, which is computed in real time.
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Langerwisch, M., Wagner, B. (2012). Guaranteed Mobile Robot Tracking Using Robust Interval Constraint Propagation. In: Su, CY., Rakheja, S., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2012. Lecture Notes in Computer Science(), vol 7507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33515-0_36
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DOI: https://doi.org/10.1007/978-3-642-33515-0_36
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