General guiding model for mobile robots and its complexity reduced neuro-fuzzy approximation

Research output: Paper

10 Citations (Scopus)

Abstract

The development of techniques for autonomous mobile robot navigation has been in focus for several decades. The main objectives of this paper are twofold. One is to extend the potential based guiding (PBG) model to a more general form that can be approximated by a common type neuro-fuzzy algorithm. The extended model eliminates the strongly alternating behavior of PBG. The second is to propose a computation complexity reduction method for the general form of the neuro-fuzzy technique. Same examples are given to show the effectiveness of the extended guiding model.

Original languageEnglish
Pages1029-1032
Number of pages4
Publication statusPublished - jan. 1 2000
EventFUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems - San Antonio, TX, USA
Duration: máj. 7 2000máj. 10 2000

Other

OtherFUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems
CitySan Antonio, TX, USA
Period5/7/005/10/00

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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    Baranyi, P., Nagy, I., Korondi, P., & Hashimoto, H. (2000). General guiding model for mobile robots and its complexity reduced neuro-fuzzy approximation. 1029-1032. Paper presented at FUZZ-IEEE 2000: 9th IEEE International Conference on Fuzzy Systems, San Antonio, TX, USA, .