Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Omniview-based concurrent map building and localization using adaptive appearance maps
Ist Teil von
2005 IEEE International Conference on Systems, Man and Cybernetics, 2005, Vol.4, p.3510-3515 Vol. 4
Ort / Verlag
IEEE
Erscheinungsjahr
2005
Quelle
IEEE Electronic Library (IEL)
Beschreibungen/Notizen
This paper describes a novel omnivision-based concurrent map-building and localization (CML) approach which is able to robustly localize a mobile robot in a uniformly structured, maze-like environment with changing appearances. The presented approach extends and improves known appearance-based CML techniques in a few essential aspects. For example, an advanced learning scheme in combination with an active forgetting is introduced to allow a complexity restricting adaptation of the environment model to appearance variations of the operation area. Moreover, a generalized scheme for fusion of localization hypotheses from several state estimators with different meaning and certainty and a distributed coding of the current observation by a weighted set of reference observations is proposed. Finally, several real-world localization experiments investigating the stability and localization accuracy of this novel omnivision-based CML technique for a highly dynamic and populated operation area, a home store, are presented.