Review of Hybridizations of Kalman Filters with Fuzzy and Neural Computing for Mobile Robot Navigation

Authors:
Manuel Graña;Iván Villaverde;Jose Manuel Guede;Borja Fernández
Affiliations:
Grupo de Inteligencia Computacional, UPV/EHU,;Grupo de Inteligencia Computacional, UPV/EHU,;Grupo de Inteligencia Computacional, UPV/EHU,;Grupo de Inteligencia Computacional, UPV/EHU,
Venue:
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Year:
2009

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Abstract

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.