Self-Localization in Dynamic Environments

  • 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 precisionof 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.

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Metadaten
Verfasser*innenangaben:Uwe R. Zimmer
URN:urn:nbn:de:hbz:386-kluedo-2968
Dokumentart:Preprint
Sprache der Veröffentlichung:Englisch
Jahr der Fertigstellung:1995
Jahr der Erstveröffentlichung:1995
Veröffentlichende Institution:Technische Universität Kaiserslautern
Datum der Publikation (Server):03.04.2000
Freies Schlagwort / Tag:artificial neural networks; mobile robots; self-localization; self-organization; world modelling
Quelle:IEEE/SOFT International Workshop BIES95 May 30 - 31, 1995, Tokyo, Japan
Fachbereiche / Organisatorische Einheiten:Kaiserslautern - Fachbereich Informatik
DDC-Sachgruppen:0 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Lizenz (Deutsch):Standard gemäß KLUEDO-Leitlinien vor dem 27.05.2011