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研究生:韓伯炫
研究生(外文):Po-HsuanHan
論文名稱:機械手臂動態分析、視覺引導、及感測器網路整合於智慧工廠之應用
論文名稱(外文):Dynamic Analysis, Vision Guidance, and Sensor Networking of Robot Manipulators for Smart Factory Applications
指導教授:陳國聲
指導教授(外文):Kuo-Shen Chen
學位類別:碩士
校院名稱:國立成功大學
系所名稱:機械工程學系
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:159
中文關鍵詞:智慧工廠機械手臂動態模型視覺引導感測器應用多機整合人機互動
外文關鍵詞:Smart FactoryRobot ManipulatorsDynamic ModelVision GuidanceSensor ApplicationMulti-machine IntegrationHuman-robot Interaction
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近年來在工業4.0的推動下,建立智慧工廠成為業界共同的目標,力求產線自動化、資訊數位化、流程智慧化。德國BOSCH Rexroth所建立的mMS4.0系統涵蓋智慧製造中的各式應用,主要由三個彼此相連的工作站展示組合件的檢測、組裝、倉儲的一條龍產線,儼然是一個縮小版的智慧工廠,然而考量到實際場域中的工作站的離散配置,mMS4.0系統的架構顯得過於理想,因此本研究提出一個以機械手臂應用為核心之智慧工廠架構,並將智慧工廠的應用情境以機械手臂為主體進一步延伸出機械手臂運動模擬、機械手臂整合視覺、感測器應用與機台狀態監控、多機整合與人機互動等四個研究分支。在機械手臂運動模擬中,本文針對利茗機械手臂進行運動學與動力學分析,並建立三維模擬介面與動態模型,接著針對機械手臂與視覺的整合,本研究以間接校正的方式將機器人座標系與視覺座標系疊合,進而形成一個視覺引導系統,在感測器應用與機台狀態監控的分支,本研究除了針對感測器發展延伸應用,亦以既有軟體工具建立監控面板,將內部機台資訊與外部感測器訊號進行整合,針對多機整合與人機互動的部分,本研究透過物聯網工具建立機台間的資料交換機制,並以利茗機械手臂與無人搬運車的搬運情境為例進行實現,同時引入外部感測器使機械手臂取得感知人員靠近的功能,建立智慧工廠中人機互動的安全機制。綜合以上的研究結果,本文將機械手臂作為主要載台,以較低的成本實現智慧工廠的要素,期望本研究的方法與成果在未來可作為中小企業在使用機械手臂升級產線時的參考。
A modified framework of smart factory centering on industrial robot applications is proposed in this work. Under this framework, the scenarios of smart factory are realized by implementing dynamic modelling, vision guidance, sensor networking, status monitoring, multi-machine integration, and human-robot interaction. For dynamic modelling of robot manipulators, a 3D simulation interface and a dynamic model are built based on kinematic and dynamic analysis. For integrating robot manipulator with vision system, an indirect calibration method is conducted to set up a reference frame for both the robot system and the vision system, resulting in a vision guided robot system. For sensor networking and status monitoring, sensor fusion is studied as well as a dashboard is built for integrating internal information from machine controllers with external data from sensors. To achieve multi-machine integration and human-robot interaction, the IoT platforms are utilized for establishing the communication mechanism among different equipment. Furthermore, the industrial robot and automated guided vehicle are integrated to implement an object transportation scenario. In addition, external sensors are integrated so that the industrial robot can sense the approaching of human beings. Hence, the safety mechanism for the human-robot interaction can be established. Eventually, by using industrial robot as a platform, the smart factory scenarios can be realized. It is believed that the methodologies and results developed in this work can be applied to fulfill smart factory in a pragmatic way in the future.
摘要 I
Abstract II
Extended Abstract III
致謝 XXII
目錄 XXIV
表目錄 XXVIII
圖目錄 XXIX
符號說明 XXXVI
第一章 緒論 1
1.1 前言 1
1.2 文獻回顧 6
1.3 研究動機與目的 9
1.4 研究方法 11
1.5 全文架構 12
第二章 研究背景 14
2.1 本章介紹 14
2.2 工業機器人簡介 15
2.3 機械手臂運動學與動力學 20
2.4 機器視覺與手眼校正 26
2.5 物聯網與工業通訊協定 30
2.6 本章結論 35
第三章 整體研究概念設計 36
3.1 本章介紹 36
3.2 情境設計 37
3.3 機械手臂運動模擬 40
3.4 機械手臂整合視覺 42
3.5 感測器應用與機台狀態監控 44
3.6 多機整合與人機互動 45
3.7 本章結論 46
第四章 機械手臂運動模擬 47
4.1 本章介紹 47
4.2 運動學分析 49
4.3 運動學模擬介面 56
4.4 動力學分析 58
4.5 動態模擬 61
4.6 路徑規劃與離線編程應用 67
4.7 初步結果討論 70
4.8 本章結論 71
第五章 機械手臂整合視覺應用 72
5.1 本章介紹 72
5.2 實驗系統建立 74
5.3 視覺系統校正與定位測試 78
5.4 座標系疊合方法 81
5.5 性能測試與比較 84
5.6 測試結果討論 89
5.7 本章結論 90
第六章 感測器應用與機台狀態監控 91
6.1 本章介紹 91
6.2 機台與感測器資訊整合 93
6.3 監控面板建立 96
6.4 感測器資訊分析與應用 99
6.5 測試結果討論 104
6.6 本章結論 105
第七章 多機整合與人機互動106
7.1 本章介紹 106
7.2 多機整合情境 108
7.3 軟體基礎與資料整合 113
7.4 工業機器人與無人搬運車配合 115
7.5 人機互動安全機制建立 119
7.6 智慧搬運整合情境 122
7.7 測試結果討論 124
7.8 本章結論 125
第八章 研究結果與討論 126
8.1 全文歸納 126
8.2 討論 130
8.3 未來工作 134
第九章 結論與未來展望 138
9.1 本文結論 138
9.2 本文貢獻 140
9.3 未來展望 142
參考文獻143
附錄 148
A Euler-Lagrange formulation(以2R Manipulator為例) 148
B 利茗機械手臂性能規格 150
C 運動學模型演算MATLAB code 152
D 機械手臂運動方程式演算MATLAB code 155
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