A new sonar salient feature structure for EKF-based SLAM

Se Jin Lee, Jae Bok Song

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

    13 Citations (Scopus)

    Abstract

    Not all line or point features capable of being extracted by sonar sensors from cluttered home environments are useful for simultaneous localization and mapping (SLAM) due to their ambiguity. We present a new sonar feature structure suitable for a cluttered environment and the extended Kalman filter (EKF)-based SLAM scheme. The key concept is to extract circle feature clouds on salient convex objects by sonar data association. The centroid of each circle cloud, called a sonar salient feature, is used as a natural landmark for EKF-based SLAM. After completing initial exploration in an unknown environment, SLAM-able areas with sonar salient features can be defined, and cylindrical objects are placed conveniently at weak SLAM-able areas as a supplemental environmental saliency to enhance SLAM performance. Experimental results demonstrate the validity and robustness of the proposed sonar salient feature structure for EKF-based SLAM.

    Original languageEnglish
    Title of host publicationIEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings
    Pages5966-5971
    Number of pages6
    DOIs
    Publication statusPublished - 2010
    Event23rd IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Taipei, Taiwan, Province of China
    Duration: 2010 Oct 182010 Oct 22

    Publication series

    NameIEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings

    Other

    Other23rd IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010
    Country/TerritoryTaiwan, Province of China
    CityTaipei
    Period10/10/1810/10/22

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Human-Computer Interaction
    • Control and Systems Engineering

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