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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/96121

    Title: A Stereo Vision-Based Self-Localization System
    Authors: Chiang, Jen-Shiun;Hsia, Chih-Hsien;Hsu, Hung-Wei
    Contributors: 淡江大學電機工程學系
    Keywords: Back propagation neural network;humanoid robot;self-localization;stereo vision
    Date: 2013-05
    Issue Date: 2014-03-03 09:35:49 (UTC+8)
    Publisher: Piscataway: Institute of Electrical and Electronics Engineers
    Abstract: This paper proposes a new stereo vision-based self-localization system (SVBSLS) for the RoboCup soccer humanoid league rules for the 2010 competition. The humanoid robot integrates information from pan/tilt motors and stereo vision to accomplish the self-localization and measure the distance from the robot to the soccer ball. The proposed approach uses a trigonometric function to find coarse distances from the robot to the landmark and from the robot to the soccer ball, after which it adopts an artificial neural network technique to increase the precision of the distance measurement. A statistics approach is also used to calculate the relationship between the humanoid robot and the position of the landmark for self-localization. The experimental results indicate that the SVBSLS localization system in this paper had an accuracy ratio of 100 for localization. The average error of distance from the humanoid soccer robot to the soccer ball was only 0.64 cm.
    Relation: IEEE Sensors Journal 13(5), pp.1677-1689
    DOI: 10.1109/JSEN.2013.2240449
    Appears in Collections:[電機工程學系暨研究所] 期刊論文

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