Near-optimal fuzzy systems using polar clustering: Application to control of vision-based arm-robot

Young Joong Kim, Myotaeg Lim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a design algorithm to near-optimal fuzzy systems using polar clustering method for vision-based robot control systems. The complexity of the optimal fuzzy system for a vision-based control system is so great that it can not be applied to real systems or can not be useful. Therefore we generally use clustering method, to reduce the complexity of optimal fuzzy systems. In the class of near-optimal fuzzy systems, for more efficient use of clustering, we propose the polar clustering method using polar quantization. In order to verify the effectiveness of the proposed method, experimentally, it is applied to a vision-based arm robot control system.

Original languageEnglish
Title of host publicationKnowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings
PublisherSpringer Verlag
Pages518-524
Number of pages7
ISBN (Print)354028897X, 9783540288978
DOIs
Publication statusPublished - 2005
Event9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005 - Melbourne, Australia
Duration: 2005 Sept 142005 Sept 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3684 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005
Country/TerritoryAustralia
CityMelbourne
Period05/9/1405/9/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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