由於科技發展使得人類生活邁入都市化的影響之下，而產生了許多的垃圾是必須急迫解決的環境問題。而為了解決該環境問題除了節約能源外，另一個常見的作法即是資源回收。目前進行資源回收的常見方法都是以人工方式撿拾分類，但此作法卻又衍生出了該行業人員的反覆性運動肌骨傷害的問題。因此近年來有許多專家學者發展以機器人進行資源回收的研究，然而卻都有受到環境限制或是工作空間不足的限制。有鑑於此，本論文旨在發展一機器人系統，協助解決人們在進行資源回收時必須反覆的抓取物件與分類的問題，及克服目前各研究中所受到的限制問題。本研究自製一台帶有機械手臂的移動型機器人，並架設攝影機作為環境資訊的回授，當攝影機辨識並計算出相對位置誤差後，會將其誤差傳送給機器人系統，使機器人主動移動至機械手臂的工作範圍內，以便用機械手臂達成擷取的目的；本研究也設計一個模組化分類控制核心，並搭配自製機構協助解決物品分類的問題，未來如需針對不同的物件進行分類，也僅需將該模組化核心替換即可，無須重新開發系統。本研究最後藉由在一個大範圍內隨機丟置未知種類的飲料罐進行多次資源回收實驗，統計此機器人系統整體成功率約為44%。

　　Recycling is a common way to deal with the increasing garbage problem in current society. However, repetitive artificial recycling actions have been recognized as one of major reasons which cause physical damage for workers. Although recently a number of researchers have developed different kinds of robotic systems to perform recycling task, the practicability is still limited by the working space in most available systems. The goal of this study is to develop a robotic system which can autonomously grasp the targeted drink cans and perform classification for large working area recycling application. The developed system consists of a hand-made mobile robot as moving platform, three webcams for vision feedback, a 6 D.O.F. robot manipulator for grasping, and a sensor module for can classification. Once the camera receives the captured image, the system first reaches the target within an acceptable region and then catches the target using the robot manipulator. Finally, the classification system automatically sorts the garbage can, delivered to each classified partition box. The random throwing experiment in a large area for four different garbage cans shows that our developed robotic system has about 44% overall successful rate.

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