本研究旨在發展一套自動化剛性曲線即時估測系統，經由目標物影像定位後，藉由夾取物品，量測物品的剛性曲線，並線上擬合其曲線方程式做後續相關運用。本研究使用機械手臂結合影像伺服演算法追蹤物品位置，再運用機械視覺與編碼器回傳的資訊，經由擴張型卡爾漫濾波器將兩種感測器的資訊進行融合，以得到更加準確的夾取壓縮量。安裝在手臂夾爪前端的力量感測器則用來量測夾取的力量，根據量得的力量與位置，畫出物體的剛性曲線，之後再運用最小平方回歸法進行曲線擬合獲得當下物品的剛性曲線方程式。實驗結果證實本系統的可行性。

This research aims to develop an on-line stiffness estimation system which can find a mathematical expression of stiffness property of the grasped object by using sensor fusion technique. This study uses a robot manipulator and visual servo control to autonomously grasp the object. In order to increase the accuracy of the object compression values, an Extended Kalman Filter is applied to fuse the data obtained from the webcam and encoder. Moreover, the grasping forces are measured by a low cost force sensor installed on the jaw of the manipulator. The force and position data are then used to find the stiffness property of the object. An on-line least square method is applied to find the stiffness equation with time-varying parameters. The experimental results verify the feasibility of the proposed method.

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