English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 53757/88386 (61%)
造訪人次 : 10525407      線上人數 : 27
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/96435

    題名: Self-Localization of a Small-Size Humanoid Soccer Robot Based on Natural Image Features
    作者: Wang, Jen-Wei;Chang, Che-Ming;Hung, Duen-Yan;Chen, Yu-Cheng;Wang, Yin-Tien
    貢獻者: 淡江大學機械與機電工程學系
    關鍵詞: Self-localization;Soccer robot;Feature detection;Feature tracking
    日期: 2008-11
    上傳時間: 2014-03-07 11:39:19 (UTC+8)
    摘要: In this paper, an EKF-based robot self-localization is developed for a small-size humanoid robot navigating in environments with natural features. A novel algorithm for feature initialization is proposed for the EKF localization algorithm: the beacon positions are firstly obtained by extracting natural and apparent features from the image taken by a monocular vision. Then the "bad" feature points are detected and abandoned before they are chosen to be a reference beacon. Meanwhile, each obstacle in the environment is detected by gathering together a set of nearby features. A regional feature detection method is also employed to detect the obstacle for comparison. The developed algorithm is implemented on a PC-based controller for a small-size humanoid robot which has dimension of 40cm in height and 3kg in weight. Experimental results show that the proposed self-localization and obstacle detection algorithms have good performance for the humanoid robot navigating in the environment with natural features.
    關聯: Proceedings of the 2008 CACS International Automatic Control Conference,6pages
    顯示於類別:[機械與機電工程學系暨研究所] 會議論文


    檔案 大小格式瀏覽次數
    Self-Localization of a Small-Size Humanoid Soccer Robot Based on Natural Image Features_英文摘要.docx13KbMicrosoft Word108檢視/開啟



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