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
    • General Computer Science

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