Self-Localization in Dynamic Environments
IEEE/SOFT International Workshop BIES'95 May 30 - 31, 1995, Tokyo, Japan
Uwe R. Zimmer
Self-localization in unknown environments respectively correlation of current and former impressions of the world is an essential ability for most mobile robots. The method, proposed in this article is the construction of a qualitative, topological world model as a basis for self-localization. As a central aspect the reliability regarding error-tolerance and stability will be emphasized. The proposed techniques demand 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-localization, self-organization, world-modelling
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