近十年來，機器人相關技術的應用已從工廠自動化延伸至日常生活
中。例如：機器人可於家庭、辦公室、和醫院等日常生活環境中協助人
類。而近幾年來，為了滿足消費者的需求，擁有擬人的外形、具親和力
的設計，及在人類生活環境中的智能等要素的各式人形機器人已被開發
了出來。本研究以實驗室所建構的一個用於打乒乓球的人形機器人，作
為一個視覺導引物件搬運研究平台，其主要由一輪式移動平台、架於移
動平台上的三自由度身軀、二個七自由度的機械手臂、一個七自由度的
機械右手掌、一個二自由度的機械左手掌及一個七自由度的雙眼機械頭
所組成。在雙眼機械頭的眼部機構中，每組眼部都配有兩個CCD 攝影機，
放置在上方的針孔攝影機為寬視野攝影機，下方的則是窄視野攝影機。
而機械頭上的兩組共四個攝影機，組成一個共平面的類複眼。本研究的
主要目標為藉由複眼機械頭以及機械手臂，以位置為基礎的看而後動的
控制策略賦予人形機器人達到物件搬運的功能。為了達成這個目標，所
需的技術包括影像處理中的邊緣偵測、中心點偵測，攝影機內外部參數
的校正，以及最小平方法等。最後經由實驗將目標物放置在不同位置，
藉由控制機械左手掌的逼近及抓取來評估他的定位性能。實驗結果指出
藉由視覺導引的控制策略可使人形機器人完成物件搬運的任務。

In recent decades, robot technology has extended from manufacturing applications to daily life. For instance, robots that assist humans in daily environments, such as in offices, homes and hospitals, are highly desired. Several humanoid robots have been developed in recent years to meet these consumer demands. A humanoid robot that was constructed to play ping-pong is adopted as a research platform for vision-guided material handling. The robot comprises mainly a wheeled mobile base, a torso with a 3 degrees of freedom (D.O.F.) waist mounted on the mobile base, two 7 D.O.F. robot arms, one 7 D.O.F. robotic
right hand, one 2 D.O.F. robotic left hand and one 7 D.O.F. robotic binocular head. In the eye mechanism of the robotic binocular head, each fully assembled eye consists of two
color CCD cameras, the upper lipstick camera capturing a wide-angle peripheral view and the lower camera capturing a narrow-angle view of the central area. Accordingly, these
four cameras of the robotic head are arranged to be a coplanar compound-like eye. The objective of this thesis is to propose a position-based look-and-move control strategy to equip the humanoid robot with the capability of handling the material by the robot arm using the compound-like eye of the robotic head. Numerous techniques are required for
implementing such a capability, including edge detection, corner and centroid detection, camera model calibration, and least-squares estimation. Finally, the positioning performance of the humanoid robot is experimentally evaluated by controlling the robotic left hand to approach and grasp a workpiece in various locations on a table. Experimental results reveal that the proposed vision-guided control strategy ensures the humanoid robot can perform pick-and-place operations.

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