A Hybrid Approach for Robust and Precise Mobile Robot Navigation with Compact Environment Modeling

In this paper a new localization approach combining the metric and topological paradigm is presented. The main idea is to connect local metric maps by means of a global topological map. This allows a compact environment model which does not require global metric consistency and permits both precision and robustness. The method uses a 360 degree laser scanner in order to extract lines for the metric localization and doors, discontinuities and hallways for the topological approach. The approach has been widely tested in a 50 x 25 m portion of the institute building with the new fully autonomous robot Donald Duck. 25 randomly generated test missions have been performed with a success ratio of 96% and a mean error at the goal point of 9 mm for an overall trajectory length of 1.15 km. Future work will focus on a similar hybrid approach for simultaneous localization and automatic mapping.