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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Review of Hybridizations of Kalman Filters with Fuzzy and Neural Computing for Mobile Robot Navigation
verfasst von : Manuel Graña, Iván Villaverde, Jose Manuel López Guede, Borja Fernández
Erschienen in: Hybrid Artificial Intelligence Systems
Verlag: Springer Berlin Heidelberg
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Kalman Filters (KF) are at the root of many computational solutions for autonomous systems navigation problems, besides other application domains. The basic linear formulation has been extended in several ways to cope with non-linar dynamic environments. One of the latest trend is to introduce other Computational Intelligence (CI) tools, such as Fuzzy Systems or Artificial Neural Networks inside its computational loop, in order to obtain learning and advanced adaptive properties. This paper offers a short review of current approaches.