English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 49633/84879 (58%)
造訪人次 : 7697110      線上人數 : 74
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/987654321/111422

    題名: 使用三維全景重建法進行電腦視覺導航
    其他題名: Computer vision based navigation with 3D scene reconstruction
    作者: 李柏儀;Lee, Po-Yi
    貢獻者: 淡江大學航空太空工程學系碩士班
    蕭富元;Hsiao, Fu-Yuen
    關鍵詞: 立體視覺;影像處理;SSD 演算法;特徵點校正;影像幾何中心校正;Stereo Vision;image processin;SSD algorithm;feature point correction;image correction of the geometric center control
    日期: 2016
    上傳時間: 2017-08-24 23:52:27 (UTC+8)
    摘要: 本論文主要探討利用三維全景建構的方式,來進行無人機的電腦視覺導航。傳統上無人機大多使用GPS 與中途點的方式來進行導航,但GPS 訊號在室內容易因為被建築物擋住而接收不到。所以在本研究中,利用建構無人機四周的三維空間資訊,找出空間中“最深”的點,並假設該點應該是走道或是任何開口,因而可以用來探索整棟建築物裡面的空間。研究時,我們比較不同的三維全景建構演算法,並尋找出空間中最深處的點,不斷透過影像處理的基礎方法提升準度及效率。在三維全景建構模擬與室內通道行走的實驗來展示本研究的可行性。本論文的成果將來可擴充無人機在室內的應用性。
    This thesis investigates the computer-vision based navigation of an unmanned aerial vehicle (UAV) using 3D scene reconstruction. Conventionally, UAVs are usually navigated with GPS signal and waypoints. This method does not work indoors, since most of GPS signal is usually blocked by buildings. In this research, we intend to navigate the UAV by constructing the 3D information
    of the environment centered at the vehicle, and find the ”deepest point” in the scene, which is presumed to be the hallway or an opening, and can be utilized to explore the build. Different algorithms of 3D scene reconstruction are compared in this thesis, and an algorithm to obtain the deepest point in space is developed. Numerical simulations and experiments are demonstrated to verify the feasibility of our algorithm. Results in this these is potentially extendable to the indoor applications of UAVs.
    顯示於類別:[航空太空工程學系暨研究所] 學位論文


    檔案 描述 大小格式瀏覽次數



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