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.
Verfasser*innenangaben: | Uwe R. Zimmer |
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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 |