本文提出了一種使用結合立體視覺和結合模糊控制器的視覺伺服方式(IBVSFC)，讓具7個自由度的工業型機械手臂可全自主式地抓取隨機位置擺放的靜止矩形物件。首先使用OpenCV軟體和顏色濾波程式過濾出特定目標物的顏色特徵，然後再以立體視覺計算目標物的三維坐標。接著透過該空間座標，反運動學公式將引導機械手臂的夾爪抵達物件的約略位置。最後再以IBVSFC調整手臂末端上抓取裝置的朝向讓它跟矩形物件的朝向一致，以便做出成功的抓取。透過7個自由度工業機器手臂在真實環境中測試可證明系統演算法之精確度和強健性都是有效的。雖然本研究的應用目前只展示抓取簡單矩形物件，但同樣的方法可以很容易地套用到抓取具其他幾何形狀的立體物體

This dissertation presents a new grasping method in which a 6-DOF industrial robot can autonomously grasp a stationary, randomly positioned rectangular object using a combination of stereo vision and image-based visual servoing with a fuzzy controller (IBVSFC). First, an openCV software and a color filter algorithm are used to extract the specific color features of the object. Then, the 3D coordinates of the object to be grasped are derived by the stereo vision algorithm, and the coordinates are used to guide the robotic arm to the approximate location of the object using inverse kinematicss. Finally, IBVSFC precisely adjusts the pose of the end-effector to coincide with that of the object to make a successful grasp. The accuracy and robustness of the system and the algorithm were tested and proven to be effective in real scenarios involving a 6-DOF industrial robot. Although the application of this dissertation is limited in grasping a simple cubic object, the same methodology can be easily applied to objects with other geometric shapes.

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