近十年來，機器人技術正由製造領域擴展至我們的日常生活，例如:人們非常期待機器人可於辦公室、家庭和醫院等日常生活環境中，協助人類。為滿足消費者的需求，近幾年來，已開發出各式各樣的服務用機器人;而人們對於多功能服務用機器人的需求已逐漸地增加。本實驗室去年建構了一個餵食用人形機器人，其主要是由一全方向輪式移動平台、一個架於輪式移動平台上的固定式身軀、兩個各七自由度的機械手臂、兩個機械手及一個安裝著全景式攝影機與二維旋轉攝影機之機械頭所組成。本論文之目的為提出一個視覺導引之控制策略，藉以賦予此一人形機器人以頭部之二維旋轉式攝影機導引協調之雙手臂搬運物件的能力。而所提出的控制策略則是基於倒傳遞類神經網路，此神經網路是用來獲得目標物之六個事先定義的影像特徵與其姿態之映射；經訓練完成後，機器人即可精確的定位出目標所在。對於物件搬運的工作，實驗結果顯示，機器人能以協調之雙手臂握持、運送與堆疊工件。

In the recent decade, the robot technology is extending the activity from the manufacturing site to our daily life. For instance, robots that assist humans in daily environments such as in offices, homes and hospitals are highly desired. To fulfill these consumer demands, several service robots have been developed in recent years. Demand for multi-functional service robots is increasing. A feeding humanoid robot that was constructed to support those who are unable to eat independently comprises mainly an omni-directional wheeled base, a fixed torso mounted on the mobile base, two 7 D.O.F. robot arms, two robot hands and a head equipped with a panoramic camera and a pan/tilt camera. The objective of this thesis is to propose a vision-guided control strategy to equip the humanoid robot with the ability to handle the material by two coordinated arms with the pan/tilt camera of the robotic head. The proposed control strategy is based on the back-propagation neural network, which is utilized to attain the mapping between six predefined image features of a target and the pose of the target. After the training stage, the robot is capable of locating the target accurately. In the task of material handling, the experimental results reveal that the robot can drive its two coordinated arms to hold, transport and stack workpieces.

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