A faster path planner using accelerated particle swarm optimization

Abdullah Zawawi Mohamed, Sang Heon Lee, Hung Yao Hsu, Namrata Nath

    Research output: Contribution to journalArticle

    17 Citations (Scopus)

    Abstract

    The idea of placing small mobile robots to move around in a large building to detect potential intruders has been around for some time. However, there are still two major hurdles to overcome: to locate itself in the environment and to make a decision on how to move around safely and effectively at a reasonable computation cost. This paper describes a mathematical model for developing a scheme for an autonomous low cost mobile robot system using visual simultaneous localization and mapping and accelerated particle swarm intelligent path planner. The results indicated that this system could provide a solution for the problem of indoor mobile robot navigation. Advances in computer technology make this technique a cost effective solution for a future home service robot.

    Original languageEnglish
    Pages (from-to)233-240
    Number of pages8
    JournalArtificial Life and Robotics
    Volume17
    Issue number2
    DOIs
    Publication statusPublished - Dec 2012

    Fingerprint

    Mobile robots
    Particle swarm optimization (PSO)
    Costs and Cost Analysis
    Costs
    Navigation
    Theoretical Models
    Robots
    Mathematical models
    Technology

    Keywords

    • Artificial intelligence
    • Global path planning
    • Local path planning
    • SLAM
    • Swarm robotics

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Biochemistry, Genetics and Molecular Biology(all)

    Cite this

    A faster path planner using accelerated particle swarm optimization. / Mohamed, Abdullah Zawawi; Lee, Sang Heon; Hsu, Hung Yao; Nath, Namrata.

    In: Artificial Life and Robotics, Vol. 17, No. 2, 12.2012, p. 233-240.

    Research output: Contribution to journalArticle

    Mohamed, Abdullah Zawawi ; Lee, Sang Heon ; Hsu, Hung Yao ; Nath, Namrata. / A faster path planner using accelerated particle swarm optimization. In: Artificial Life and Robotics. 2012 ; Vol. 17, No. 2. pp. 233-240.
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