Robust World-Modelling and Navigation in a Real World
Neurocomputing, Vol. 13, Nos. 2-4, pp. 247-260, 1996
Uwe R. Zimmer
This article will discuss a qualitative, topological and robust world-modelling technique with special regard to navigation-tasks for mobile robots operating in unknown environments. As a central aspect, the reliability regarding error-tolerance and stability will be emphasized. Benefits and problems involved in exploration, as well as in navigation tasks, are discussed. The proposed method demands very low constraints for the kind and quality of the employed sensors as well as for the kinematic precision of the utilized mobile platform. Hard real-time constraints can be handled due to the low computational complexity.
The principal discussions are supported by real-world experiments with the mobile robot 'ALICE'.
keywords: artificial neural networks, mobile robots, self-organization, world-modelling, navigation
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