Review of hybridizations of kalman filters with fuzzy and neural computing for mobile robot navigation

  • Manuel Graña*
  • , Iván Villaverde
  • , Jose Manuel López Guede
  • , Borja Fernández
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationHybrid Artificial Intelligence Systems - 4th International Conference, HAIS 2009, Proceedings
Pages121-128
Number of pages8
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event4th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2009 - Salamanca, Spain
Duration: 10 Jun 200912 Jun 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5572 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2009
Country/TerritorySpain
CitySalamanca
Period10/06/0912/06/09

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