本研究結合有限元素分析軟體Ansys與布穀鳥搜尋演算法，開發一套可適於氣動軟性致動器的尺寸最佳化設計流程，致動器使用矽膠材料以氣壓輸入作為力量來源，並結合五個致動器，製作出一組模仿人類手部的氣動軟性機器手。本研究將致動器區分為實心體與氣囊設計，各代表不可彎曲的指節與可彎曲的關節構造，並以彎曲最大化為目標函數，針對氣囊結構分別進行正壓、負壓、與同時包含正負壓的複合式條件的尺寸最佳化。在最佳化過程中使用有限元素分析軟體Ansys計算目標函數，將氣囊化簡為四分之一模型以降低運算時間，經過比較挑選，複合式條件中權重比為0.5的尺寸結果在正壓與負壓的綜合彎曲表現最佳，並以此結果進行致動器實體的試做。完成製作後，本研究先對單一致動器進行空負載的彎曲測試與驗證，正壓彎曲與模擬的平均誤差為9.6%，最大壓力35kPa下末端點彎曲角度可達110^o；負壓彎曲與模擬的平均誤差僅為2.4%，最大壓力-20kPa下末端點彎曲角度可達28^o，而單一致動器在正壓50kPa的輸入下推力最大為0.7N。最後將五個致動器組為氣動軟性機器手，以兩種方向對機器手進行負重測試，在50kPa的氣壓輸入下，垂直抓握最大負重為2.17kg，平行抓握最大負重為0.66kg，最大開度透過負壓輸入可提升4.35倍，最大夾取尺寸為直徑150mm之圓球，並進行多種實物夾取與人類手部姿態的模仿實驗，結果顯示本研究的機器手設計，在整體抓握姿態與人類手掌展現出良好的吻合度。

This study presents a size optimization method that combines the finite element analysis software ANSYS and the cuckoo search algorithm to design a soft pneumatic actuator. In addition, a soft pneumatic robotic hand is designed by combination of five actuators which are made of silicone material through the molding process. In order to mimic the human fingers, this study divides an actuator into two parts. One is the solid bodies that symbolize the bones of fingers；the other is air chambers that symbolize the finger joints. The main goal in this study is to maximize the bending ability. The air chamber is the design domain, and its geometric parameters are design variables. The size optimization is executed under three different conditions including positive pressure, negative pressure, and the compound condition with both positive and negative pressure. The bending tests of the actuator, payload and grasping tests of the robotic hand were implemented. Experimental results show that the average error between experiment and simulation is 9.6% at positive pressure and 2.38% at negative pressure. The maximum bending angle is 110 degrees at 35kPa, and 28 degrees at -20kPa. The payload tests can be divided into two categories. One is perpendicular to the direction of gravity, the other is parallel to the direction of gravity. The maximum payloads are 2.17kg and 0.66kg respectively, when the pressure is 50kPa. Because of the consideration of the negative pressure, the maximum gripping range is increased by 4.35 times. After grasping tests, the design of the robotic hand in this study shows good fit with human hand in most grasping postures.

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