An Integrative Framework for Global Self-Localization

2001 IEEE Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2001)
Baden-Baden, Germany, August 20-22, 2001

Joachim Weber, Lutz Franken, Klaus-Werner Jörg, Klaus Schmitt, Ewald von Puttkamer

Concerning the robustness of mobile robot navigation, global self-localization is a key feature for many service applications. In this paper we describe an effcient Bayesian approach for hybrid topological/metric navigation, which is designed to exploit information from multiple sources of sensor data. Experiments with a combination of odometry/laserscans/computer vision in a partly monotonous environment show the system's ability to generate initial position hypotheses, to cope with environmental ambiguities and to recover from severe position errors.

Paper (pdf)

Back to Publications