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研究生:何嘉芬
研究生(外文):HE,JIA-FEN
論文名稱:人機協作環境中遞交作業等候時間之評估
論文名稱(外文):Evaluation of Waiting Times for Hand-over Tasks in Human – Robot Collaborative Environment
指導教授:唐國豪唐國豪引用關係
指導教授(外文):TANG,KUO-HAO
口試委員:洪弘祈王逸琦唐國豪
口試委員(外文):HUNG,HUNG-CHIWang,YI-CHITANG,KUO-HAO
口試日期:2017-07-28
學位類別:碩士
校院名稱:逢甲大學
系所名稱:工業工程與系統管理學系
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:中文
論文頁數:52
中文關鍵詞:機器手臂人機協作遞交作業等候時間效率
外文關鍵詞:RobotHuman - Robot CollaborationHand-over TasksWaiting TimeEfficiency
相關次數:
  • 被引用被引用:1
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人與機器人協同的工作模式,是一個正在發展中的領域。在人與機器人協作情境下,遞交作業是一個基本的互動元素之一。協作在遞交作業過程中,無論人等待機器人或機器人等待人,均構成了作業等候時間,因此人與機器人在遞交作業時的精準度、流暢度等,均影響人機協作之工作效率,本研究目的將探討機器人能準確預測遞交物件給人類的時間點,使等待時間降低、減少整體作業時間而獲得較佳之效率。
本研究利用Python程式連結UR3機器人與可即時擷取動作位置PhaseSpace,作業設計為製造系統中最典型的組裝作業,以LEGO積木作為組裝的零件。在大量生產與批量生產兩種生產模式下,改變組裝速度與組裝作業,運用三種不同遞交估計方式,分別為時間量測方法(MTM)、Sensor觸發機制、Kalman filter。量測作業時間與等待時間(人等機器人、機器人等人)以評估遞交流暢性以及工作效率。
針對不同生產型態分析結果得知,在大量生產情況下,雖然作業時間基本上一致,但由於人工操作上因牽涉到速度或組裝時間的變異,則Kalman filter預測方法優於MTM固定時間方法,可適時作調整遞交時間點,而減少機器人或人的閒置時間。在批量生產情況下,因牽涉批量間作業時間變化,而作業轉變過程中Kalman filter相對於MTM較長等待時間,因需要經過幾次組裝逐漸調整,但如果批量較大時,而Kalman filter可以適應在同一個作業時間之下的人工組裝速度變化,如同大量生產狀況一樣。

Human- robot collaboration is an emerging field of study in which hand-over being one of the basic interactive elements. During a hand-over task, task waiting time is defined as a human operator waiting for a robot or vice versa. Such waiting times determine the accuracy and fluency of a hand-over task to some extent and this study discussed the factors affecting the efficiency of a hand-over task. The objective of this thesis is to investigate the timing which enabling an accurate delivery of a robot, which, in turn, reduces waiting times and operation cycle times to get better efficiency.
This study used Python as a platform to connect a UR3 robot and a motion capture system PhaseSpace to investigate the waiting time involved in hand-over tasks. We used LEGO blocks to mimic a typical assembly task. Under the scenarios of mass production and batch production, assembly speed and assembly operations were manipulated and the delivery timing of the robot was determined by three different methods, namely, Methods of Time Measurement, Sensor trigger and Kalman filter, the operation cycle times and the waiting times were measured to assess the hand-over task fluency and efficiency.
For mass production, although the average cycle times were controlled to be the same, Kalman filter performed better than MTM as Kalman filter can adjust the delivery timing according to the variation caused by manual operation thus reduce the idle time for both robots and humans. For batch production, the cycle times changed dramatically during batch transfer. When compared with MTM, Kalman filter created longer waiting times at the beginning of a batch transfer and became more stable after a few operation cycles. This result may suggest that if a production batch is large, Kalman filter can adapt to the human assembly speed variation similar to that in mass production.

誌  謝
摘  要
Abstract
目錄
圖目錄
表目錄
第一章、緒論
1.1研究背景與動機
1.2研究目的
1.3研究流程
第二章、文獻探討
2.1人與機器人互動模式
2.2遞交作業
2.3機器人意圖預期及遞交流暢度
第三章、組裝作業遞交時間實驗量測
3.1實驗設備系統
3.1.1UR3協作型機器人
3.1.2PhaseSpace動作擷取系統
3.1.3Python API連結
3.2實驗作業及變數
3.2.1組裝作業設計與假設
3.2.2作業時間及作業等候時間之定義
3.3實驗方法
3.3.1時間量測方法(Methods of Time Measurement ,MTM)
3.3.2 Sensor觸發機制
3.3.3卡爾曼濾波器(Kalman filter)
3.4實驗程序
第四章、實驗分析與結果
4.1大量生產下組裝速度之變化
4.1.1不同遞交估計方法與組裝速度分析與結果
4.1.2組裝學習效應實驗分析與結果
4.2批量生產下組裝作業改變
4.2.1不同遞交估計方法與組裝作業改變分析與結果
4.2.2Kalman filter演算法的R值設定
4.3組裝速度與移動距離影響作業時間分析
第五章、結論與未來展望
參考文獻

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