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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 詹魁元(Kuei-Yuan Chan) | |
| dc.contributor.author | Po-Yu Chen | en |
| dc.contributor.author | 陳柏宇 | zh_TW |
| dc.date.accessioned | 2021-06-17T08:28:36Z | - |
| dc.date.available | 2019-08-16 | |
| dc.date.copyright | 2019-08-16 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-08-12 | |
| dc.identifier.citation | [1] DuPont de Nemours Inc, 2019. [Online]. Available: https://www.dupont.com/
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/74298 | - |
| dc.description.abstract | 對於機械手臂應用於高精度插件組裝任務而言，各系統座標系(如機械手臂基座、末端法蘭面、相機、工具、工件)間的轉換關係對精度影響甚鉅，然而由於元件裝配誤差、機械加工誤差等幾何或尺度的不確定因素，使得座標轉換矩陣存在著不精準性，不能依靠機構設計中的理想座標轉換矩陣，因此本論文針對垂直多關節機械手臂應用於高精度插件任務提出一套離線校正方法，本方法具高精度、高彈性、高穩健性等特點，並且能離線校正機械手臂系統間的座標轉換關係，適用於工廠生產線中不能停機校正機械手臂的限制，能異地先行校正完機械手臂系統的相機與工具，再移至生產線上執行插件任務。本方法基於影像資訊進行校正，但不仰賴影像即時回饋的方式，而是採用多姿態定點拍攝校正版，透過偵測校正版特徵之影像尺度資訊並與實際物理尺度進行相機校正與手眼校正，並以實際插件組裝任務評估精度表現。本論文之研究流程將應用於虛擬系統與真實系統之插件組裝任務做為演示及討論，於虛擬系統中以理想且所有資訊皆已知的環境驗證演算法之可行性與精準度，結果顯示在虛擬系統中機械手臂插件任務之精度表現達到 0.0706 mm 之位置精度、 0.1373 度之朝向精度，而應用於真實系統中會存在環境不確定因素，但本研究方法之穩健性高，即使是有環境雜訊與裝配誤差，仍然能達到 +-0.25 mm 之絕對精度水平，相較於未校正系統其精度高於兩倍以上。 | zh_TW |
| dc.description.abstract | Uncertainties of a robot manipulator include the inaccurate transformation between coordinates, (e.g., robot base, flange, camera, tool, and workpiece), and the inherent variations within each links and mechanical components. In this thesis, we propose an offline calibration method for vertical articulated manipulator in high precision peg-in-hole assembly tasks. Our method is based on the images captured by well-calibrated camera to detect fiducial pattern and marker. These images are then used to determinie the transformation metrics between each coordinate. The accuracy performance is evaluated by the actual peg-in-hole assembly task. The proposed method will be applied to demonstrate the peg-in-hole assembly task in virtual and real environment. In order to verify the feasibility and accuracy of the algorithm in the virtual system with an ideal environment where all information is known. The simulation results show that the accuracy of peg-in-hole assembly can reach 0.0706 mm position error and 0.1373 degree orientation error for hole locations that are not known as a priori. Even with environment noise and unit uncertainty in real system, the absolute accuracy level of +-0.25 mm can still be reached, which is more than twice as high as that of the uncalibration system. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T08:28:36Z (GMT). No. of bitstreams: 1 ntu-108-R06522615-1.pdf: 98329287 bytes, checksum: d620f3d18ccd3e4451a3996813e63678 (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
誌謝 ii 摘要 iv Abstract v 目錄 vi 圖目錄 ix 表目錄 xii 第一章 緒論 1 1.1 前言 1 1.2 機械手臂於工廠的定位與應用 1 1.3 多關節機械手臂應用於插件組裝任務 4 1.4 研究動機與研究目的 5 1.5 本文架構 7 第二章 文獻回顧 9 2.1 工業機械手臂之精準度提升方法 9 2.1.1 機械手臂不確定因素模型之參數識別 9 2.1.2 機械手臂實驗校正 11 2.1.3 小結 11 2.2 相機應用於機械手臂之校正方法 12 2.2.1 手眼校正 12 2.2.2 相機校正 14 2.2.3 小結 16 2.3 加工工具於機械手臂之校正方法 16 2.3.1 小結 18 2.4 機械手臂應用於插件組裝任務之相關文獻 18 2.4.1 視覺感測器 18 2.4.2 力/力矩感測器 19 2.4.3 末端效應器機構 19 2.4.4 無感測器 19 2.4.5 小結 20 第三章 模型建置 21 3.1 工業相機模型 21 3.1.1 針孔相機模型 21 3.1.2 鏡頭光學畸變模型 24 3.1.3 齊次座標系統 26 3.1.4 單應性矩陣 27 3.2 相機校正方法 31 3.2.1 張氏相機校正方法 31 3.2.2 變焦與對焦原理 34 3.3 機械手臂校正方法 40 3.3.1 座標系統介紹 40 3.3.2 手眼校正方法 42 3.3.3 工具中心點校正方法 43 3.3.4 工件座標校正方法 47 第四章 研究方法 49 4.1 環境建立 52 4.2 離線校正 (Offline Calibration) 56 4.2.1 機械手臂校正 (Robot Calibration) 56 4.2.2 置中 (Cetering) 57 4.2.3 對焦 (Focusing) 58 4.2.4 計算拍照位置 (Auto pose) 59 4.2.5 相機校正 (Camera Calibration) 59 4.2.6 手眼校正 (Hand/Eye Calibration) 62 4.2.7 工具中心校正 (Tool Center Point Calibration) 64 4.3 產線操作 (Online Operation) 64 4.3.1 工件孔洞搜尋 (Hole Searching) 64 4.3.2 插件 (Peg in hole) 69 4.4 精度驗證 70 第五章 工程案例 71 5.1 硬體規格與其控制環境 71 5.2 試驗條件 72 5.3 自動化校正流程 74 5.3.1 離線校正 (Offline Calibration) 74 5.3.2 產線操作 (Online Operation) 80 5.3.3 插件 (Peg in hole) 83 5.3.4 精度驗證 83 5.4 誤差來源 90 5.4.1 機械手臂本體之誤差 90 5.4.2 視覺影像之誤差 91 5.4.3 加工工具之誤差 91 5.4.4 數值計算之誤差 92 第六章 結論與未來展望 93 6.1 結論 93 6.2 研究建議與未來研究方向 94 附錄 A 程式碼 96 參考文獻 97 | |
| dc.language.iso | zh-TW | |
| dc.subject | 機械手臂 | zh_TW |
| dc.subject | 手眼校正 | zh_TW |
| dc.subject | 相機校正 | zh_TW |
| dc.subject | 離線校正 | zh_TW |
| dc.subject | 插件 | zh_TW |
| dc.subject | 組裝 | zh_TW |
| dc.subject | 最佳化 | zh_TW |
| dc.subject | Assembly | en |
| dc.subject | Optimization | en |
| dc.subject | Robot manipulator | en |
| dc.subject | Hand/Eye Calibration | en |
| dc.subject | Camera Calibration | en |
| dc.subject | Offline Calibration | en |
| dc.subject | Peg-in-Hole | en |
| dc.title | 垂直多關節機械手臂應用於高精密插件組裝任務之離線校正方法 | zh_TW |
| dc.title | Offline Calibration for Vertical Articulated Robot Manipulator in High Precision Peg-in-Hole Assembly | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 李志中(Jyh-Jone Lee),徐冠倫(Kuan-Lun Hsu) | |
| dc.subject.keyword | 機械手臂,手眼校正,相機校正,離線校正,插件,組裝,最佳化, | zh_TW |
| dc.subject.keyword | Robot manipulator,Hand/Eye Calibration,Camera Calibration,Offline Calibration,Peg-in-Hole,Assembly,Optimization, | en |
| dc.relation.page | 110 | |
| dc.identifier.doi | 10.6342/NTU201902922 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2019-08-13 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 機械工程學研究所 | zh_TW |
| 顯示於系所單位： | 機械工程學系 | |
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