Bayesian Programming for Topological Global Localization with Fingerprints

Adriana Tapus (1) , Stephan Heinzer (2) , Roland Y. Siegwart (2)

1 U2IS - Unité d'Informatique et d'Ingénierie des Systèmes
2 ASL - Autonomous Systems Lab

This work presents a localization algorithm for indoor environments. The environmental model is topological and the approach describes how a multimodal perception increases the reliability for the topological localization problem for mobile robots, by using the Bayesian programming formalism. For the topological framework the fingerprint concept is used. This type of representation permits a reliable and distinctive environment modeling. Experimental results of a mobile robot equipped with a multi sensor system composed of two 180° laser range finders and an omni-directional camera are reported.

Domaines: Robotique [cs.RO]

Adriana Tapus, Stephan Heinzer, Roland Y. Siegwart. Bayesian Programming for Topological Global Localization with Fingerprints. ICRA 2004, Apr 2004, New Orleans, United States. pp.598 - 603, ⟨10.1109/ROBOT.2004.1307214⟩. ⟨hal-01015925⟩