機器人技術過去在工業界上貢獻良多。近幾年來，從工業上的應用擴大到我們的日常生活。本論文的目標為建構一個餵食用人形機器人，以用來扶持不能獨立進食的人們。所建構之餵食用人形機器人主要包括一個全方移動的輪式底盤、架在底盤上之一個固定軀幹、兩隻各具有七自由度之機械手臂、兩個機械手，並裝置有一全景式攝影機與和一部具有旋轉/俯仰/變焦攝影機之機械頭。在執行餵食的任務時，機器人的運動主要分主要兩個階段。在第一階段的運動是以視覺導引的控制策略來確定餐盤之姿態，並應用所開發之智慧型協調阻抗控制器，此開發之控制器來進行機器人雙手協同端餐盤之動作。第二階段的運動，同樣是以視覺引導控制策略來找出被餵食者口的姿態，進而控制機器人之右手臂夾取在餐盤中之固態食物，以達到餵食之動作。所應用之視覺導引控制策略是基於倒傳遞類神經網路，主要是用來得到目標之影像特徵與目標之姿態間的映射關係。最後我們透過實驗，以驗證我們所建構之餵食用人型機器人之性能。

The robot technology contributed much to the growth of manufacturing industries. In recent years, however, it is extending the activity from the manufacturing site to our daily life. The objective of this thesis is to create a feeding humanoid robot to support those who are unable to eat independently. The constructed feeding humanoid robot comprises mainly an omni-directional wheeled base, a fixed torso mounted on the mobile base, two seven-degrees-of-freedom arms, two robot hands and a head equipped with a panoramic camera and a pan/tilt/zoom camera. In the task of feeding, the humanoid robot moves in two stages. In the first stage of movement, a vision-guided control strategy is first utilized to determine the pose of the meal tray to be carried, and a developed intelligent coordination impedance controller is then applied to drive two robot arms to carry the meal tray. In the second stage of movement, the same vision-guided control strategy is first employed to find the pose of the human mouth to be fed, and the right arm of the feeding robot is then controlled to grasp solid foods in the meal tray and feed the person with the foods. The utilized vision-guided control strategy is based on the back-propagation neural network, which is applied to achieve the mapping between image features of the target and the pose of the target. Finally, a set of experiments are conducted to verify the performance of the constructed feeding humanoid robot.

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