本研究研發一具腱張力回饋之欠驅動式五指機械手掌設計，其以仿人手指結構設計出14個關節之五隻手指，其中除了拇指具有一屈曲與伸直關節與一個內外展關節外，其餘手指均採屈曲與伸直關節。為了簡化此一機械手掌之控制架構，除了拇指外，每一手指機構採用欠驅動設計，其透過單一步進馬達連接纜線便可驅動所有關節，並可順應所接觸物體表面，以更穩固方式握取物體；而拇指關節之兩個自由度則以直接耦合驅動；因此一共有6個控制自由度。此外，為了得知每一纜線腱張力，本研究開發一3公分長之纜線張力量測模組，以藉此得知每一手指使否已達穩定握取之條件。此一腱張力回饋之握取機制有別於傳統欠驅動式機械手掌其需要事先知道握取物品之尺寸與外型以決定纜線控制長度。因此，本研究所提出之腱張力回饋機制可應用於未知外型之物品握取，大大提升握取之效率與彈性。最後，本研究將此一五指機械手掌模組連接於六軸機器手臂末端，並進行未知外型之物品1.寶特瓶_1(近似長方體型)、2.寶特瓶_2(近似圓柱體型)、3.玩具球以及4.鴕鳥蛋這四種物體之抓取，證明此一腱張力回饋五指機械手掌在握取不同物體時，每隻機械手指所需的握力都不相同，在握取較硬物體時，如：寶特瓶_1、寶特瓶_2，各指的纜線張力量測模組上FSR的設定值分別為：拇指35牛頓、食指35牛頓、中指38牛頓、無名指30牛頓以及小指35牛頓，在握取較軟物體時，如玩具球、鴕鳥蛋，各指的腱張力量測模組上FSR的設定值分別為：拇指30牛頓、食指30牛頓、中指35牛頓、無名指25牛頓以及小指30牛頓，實驗結果驗證可依不同外型與材質的物體來設定各指所需的握力，不會拘限於某個特定的握力作抓取。

　　This study develops a five-finger robotic hand with tendon force feedback. The proposed five-finger robotic hand is designed by imitating the structure of human’s hand and fingers, and it is composed of 5 fingers with 14 joints. The thumb finger consists of a flexion and extension joint and an abduction joint; the other four fingers are all designed as flexion and extension joints. Except for the thumb finger, all fingers use the underactuated mechanism to simplify the control architecture. For the finger with underactuated mechanism is controlled via a single cable trough a stepping motor. All the joints and linkages in the underactuated mechanism can be compliant to the object’s surface to perform a stable grasp. On the other hand, the two joins of the thumb finger use direct coupling mechanism. As a consequence, there are six controllable degrees of freedom in this system. To obtain the tendon force of a cable, a 3cm long cable tension measure module is specially developed to evaluate if each finger has stably grasped the object. The grasping mechanism of the tendon force feedback mechanism is different to the conventional position-based grasping, where the object shape is required in advance to defined to cable’s length to be controlled. Nevertheless, the proposed tendon force feedback can be applied to grasp the object without knowing the surface condition. Hence, the proposed tendon force feedback significantly improves the grasping efficiency and flexibility.
　　Finally, the proposed five-finger robotic hand module is connected to the end effector of a six-axis robotic arm for the experiments of grasping two hard surface objects and two soft surface objects. The hard surface objects are a round rectangular bottle, a cylindrical shape bottle; the hard surface objects are a toy balls and an ostrich egg. For grasping hard surface objects, the tendon forces of the wires connecting to the thumb, index finger, middle finger, ring finger and little finger are 35N, 35N, 38N, 30 N, and 35 N, respectively. For grasping soft surface objects, the tendon forces of the wires connecting to the thumb, index finger, middle finger, ring finger and little finger are 30N, 30N, 35N, 25 N, and 30 N, respectively. The experiment results show that the adjustable tendon force on each finger could effective grasp the objects without knowing the shapes and dimension for grasping.

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