本論文完成了使用全向式攝影機之機器人定位設計與實驗，基於 EKF SLAM 之演算法，以全向式攝影機對環境做觀測，在機器人移動的同時，能夠建立出環 境地圖並定位出機器人的位置。
在環境的觀測方面，使用全向式攝影機為感測器，利用 SIFT 特徵點辨識演 算法配合攝影機的特性，成功的擷取辨識出在影像平面上的環境特徵點，並使用 一除錯法，實驗結果特徵點辨識的正確率平均為 90%。
基於攝影機對環境特徵點的觀測，及不同地點對特徵點的觀測視角，推算出 特徵點相對於機器人本身的距離關係，並以此資訊做為定位系統的輸入。使用 SLAM 演算法解決機器人之定位及地圖建立的問題，以機器人之移動模型、攝影 機之觀測模型，達成 EKF-based SLAM 演算法。結合影像處理與 SLAM 演算法，
實現在機器人平台上，目前實驗的測試上，一次的定位系統演算法運算耗時 2 秒以內。
最後並以實際的實驗來驗證定位演算法：在來回行走共 30 公尺後之定位誤 差平均為 0.11 公尺，而情境模擬實驗的結果證實機器人能依定位系統的幫助，
從房間內走出到走廊，沿走廊移動近 50 公尺的距離後回到房間內，並且同時建 立出走廊環境的特徵點地圖，達成機器人室內導航的功能。
在本論文中之定位演算法需耗時 2 秒左右，此運算時間在較為慢速的測試實 驗中雖然可行，但若在實際的應用中對於環境可能的複雜性或是改變則不能有及 時的反應，因此在影像處理及定位演算法的設計上可以再加以改善，提升整體定 位系統的效能。
全向式攝影機常被用於多機器人系統上，而本論文發展出的基於全向攝影機 之機器人定位方法亦可與之整合，讓攝影機的功能不僅能夠觀測機器人隊伍中的 隊友，也讓機器人能對周遭整體的環境做估測，並得知所在之位置，增加多機器 人隊伍的實用與功能。
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