淡江大學機構典藏:Item 987654321/55103
English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62822/95882 (66%)
Visitors : 4028497      Online Users : 575
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/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

    Files in This Item:

    File Description SizeFormat
    1560-6686_14(2)_p123-129.pdfpaper2808KbAdobe PDF438View/Open
    index.html0KbHTML211View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback