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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/55103


    Title: Monocular SLAM for a Small-size Humanoid Robot
    Authors: Wang, Yin-tien;Hung, Duen-yan;Cheng, Sheng-hsien
    Contributors: 淡江大學機械與機電工程學系
    Keywords: Speeded Up Robust Features;SURF;Simultaneous Localization and Mapping;SLAM;Image Feature Initialization;Humanoid Robot
    Date: 2011-06-01
    Issue Date: 2011-08-11 19:39:04 (UTC+8)
    Publisher: 新北市:淡江大學
    Abstract: The paper presents a algorithm of visual simultaneous localization and mapping (vSLAM) for a small-size humanoid robot. The algorithm includes the procedures of image feature detection, good feature selection, image depth calculation, and feature state estimation. To ensure robust feature detection and tracking, the procedure is improved by utilizing the method of Speeded Up Robust Features (SURF). Meanwhile, the procedures of image depth calculation and state estimation are integrated in an extended Kalman filter (EKF) based estimation algorithm. All the computation schemes of the visual SLAM are implemented on a small-size humanoid robot with low-cost Window-based PC. Experimentation is performed and the results show that the performance of the proposed algorithm is efficient for robot visual SLAM in the environments.
    Relation: Tamkang Journal of Science and Engineering=淡江理工學刊 14(2), pp.123-129
    DOI: 10.6180/jase.2011.14.2.05
    Appears in Collections:[Graduate Institute & Department of Mechanical and Electro-Mechanical Engineering] Journal Article

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