請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/71412完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 李志中(Jyh-Jone Lee) | |
| dc.contributor.author | Tsung-Han Lin | en |
| dc.contributor.author | 林宗翰 | zh_TW |
| dc.date.accessioned | 2021-06-17T06:00:16Z | - |
| dc.date.available | 2021-02-13 | |
| dc.date.copyright | 2019-02-13 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-02-12 | |
| dc.identifier.citation | [1]B. Leon, A. Morales, and J. Sancho-Bru, “From Robot to Human Grasping Simulation,” Springer, pp. 19, 2014.
[2]劉貽仁，”機器手掌與機器手臂自動抓取規劃與軌跡規劃”，碩士論文，國立台灣大學機械工程學系，2016。 [3]K. Koyama, Y. Suzuki, A. Ming, and M. Shimojo, “Integrated Control of a Multi-fingered Hand and Arm using Proximity Sensors on the Fingertips,” presented at the IEEE ICRA, 2016. [4]D. Buchholz, M. Futterlieb, S. Winkelbach, and F. M. Wahl, “Efficient Bin-Picking and Grasp Planning Based on Depth Data,” Proceedings of the 2013 IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 2013. [5]Nguyen Thanh Hung, “3-D Object Recognition and Localization of Randomly Stacked Objects for Automation,” doctoral thesis, National Taipei University of Technology Electromechanical Technology, Taipei, Taiwan, 2015. [6]A. T. Miller, S. Knoop, H. I. Christensen, and P. K. Allen, “Automatic Grasp Planning Using Shape Primitives,” presented at the IEEE ICRA, Taipei, Taiwan, 2003. [7]蔡謹容，”以基礎幾何模型搭配具主被動自由度和掌內壓力與近接感測之夾爪達到快速低計算成本之多樣化物體夾取”，碩士論文，國立台灣大學機械工程學系，2017。 [8]D. T. Pham, and S. H. Yeo, “A Knowledge-Based System for Robot Gripper Selection: Implementation Details,” International Journal of Machine Tools and Manufacture, Vol. 28, No. 4, pp. 315-324, 1988. [9]D. T. Pham, and S. H. Yeo, “A Knowledge-Based System for Robot Gripper Selection: Criteria for Choosing Grippers and Surfaces for Gripping,” International Journal of Machine Tools and Manufacture, Vol. 28, No. 4, pp. 301-313, 1988. [10]J. D. Wolter, R. A. Volz, and A. C. Woo, “Automatic Generation of Gripping Positions,” IEEE Transactions on Systems, Man, and Cybernetics, Vol. SMC-15, No. 2, pp. 204-213, 1985. [11]G. M. Bone, A. Lambert, and M. Edwards, “Automated Modeling and Robotic Grasping of Unknown Three-Dimensional Objects,” Proceedings of the 2008 IEEE International Conference on Robotics and Automation, Pasadena, CA, USA, 2008. [12]蔡佩佳，”電腦輔助夾爪選用規劃”，碩士論文，國立臺灣大學機械工程學系，2013。 [13]盧冠妤，”結合點雲影像辨識之機器手臂夾取位置與姿態之設計”，碩士論文，國立臺灣大學機械工程學系，2018。 [14]Y. Jiang, S. Moseson, and A. Saxena, “Efficient Grasping from RGBD Images: Learning using a new Rectangle Representation,” Proceedings of the 2011 IEEE International Conference on Robotics and Automation, Shanghai, China, 2011. [15]Dex-Net. Available: <https://berkeleyautomation.github.io/dex-net/>, 2018. [16]J. Mahler et al. , “Dex-Net 1.0: A Cloud-Based Network of 3D Objects for Robust Grasp Planning Using a Multi-Armed Bandit Model with Correlated Rewards,” Proceedings of the 2016 IEEE International Conference on Robotics and Automation, Stockholm, Sweden, 2016. [17]J. Mahler et al. , “Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics,” Robotics: Science and Systems, 2017. [18]陳祥輝，TCP/IP網路通訊協定，博碩文化股份有限公司，2009。 [19]Z. Zhang, “A Flexible New Technique for Camera Calibration,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 11, pp. 1330-1334, 2000. [20]J. Heikkila, and O. Silven, “A Four-step Camera Calibration Procedure with Implicit Image Correction,” IEEE International Conference on Computer Vision and Pattern Recognition, 1997. [21]OpenCV. Camera Calibration and 3D Reconstruction. Available: <https://docs.opencv.org/2.4/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html>, 2018. [22]羅國益，”基於視覺之工業用機械手臂物件取放作業研究”，碩士論文，國立成功大學電機工程學系，2016。 [23]OpenCV. Available: <https://opencv.org/>, 2018. [24]OpenCV Wikipedia. Available: <https://zh.wikipedia.org/wiki/OpenCV>, 2018. [25]R. S. Ledley, M. Buas, and T. J. Golab, “Fundamentals of true-color image processing,” Processing of the 10th IEEE International Conference on Pattern Recognition, Vol. 1, pp. 791-795, 1990. [26]C. C. Yang, and J. J. Rodriguez, “Efficient luminance and saturation processing techniques for bypassing color coordinate transformations,” Proceedings of IEEE International Conference on Systems, Man and Cybernetics, Vol. 1, pp. 667-672, 1995. [27]L. G. Shapiro, and G. C. Stockman, 'Computer Vision,' Prentice Hall, pp. 154, 2001. [28]I. Sobel, “History and Definition of the Sobel Operator,” 2014. [29]C. Harris, and M. Stephens, 'A Combined Corner and Edge Detector,' Alvey Vision Conference, 1988. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/71412 | - |
| dc.description.abstract | 在工廠的生產線上，要進行較複雜的加工任務或物件取放任務時，機械手臂通常會導入電腦視覺系統，藉以輔助自動化產線，以提高其效率，而本論文旨在研究與開發一種基於視覺之自動化物件取放流程。
本論文使用二指平行夾爪發展出一套自動夾取流程，針對具角點的任意角柱形物體，結合影像處理並設計演算法，提供一個簡易的使用者介面，讓使用者能夠快速且有效率地執行夾取工作。此一流程首先使用一固定位置之相機拍攝物體，接著對輸入影像進行影像處理後可以獲得角柱截面的所有角點位置；再來，利用這些角點位置計算最佳之夾持點，最後命令機械手臂移動至夾持點位置並夾取物體。本研究並實際測試了多種角柱形物體，以證實本夾取流程的可行性。 | zh_TW |
| dc.description.abstract | In the production line of a factory, to perform complex machining work or object pick-and-place, a computer vision system is commonly added to assist the automated production line so as to improve the efficiency. The purpose of this thesis is to develop a vision-based automated object pick-and-place planning.
This thesis developed an automated object pick-and-place plan using two-fingered gripper. The plan, suitable for polygonal prisms with identifiable corner points, integrated image processing and design algorithm into a robotic system and provided a user interface to allow users to manipulate the robot to grip the object in a quick and efficient way. In the last, this work validated the process with a real robot. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T06:00:16Z (GMT). No. of bitstreams: 1 ntu-108-R04522617-1.pdf: 5585797 bytes, checksum: 8e36a7fd1ed077c11332c026038f173c (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
誌謝 ii 摘要 iii Abstract iv 目錄 v 圖目錄 vii 第一章 緒論 1 1.1 前言 1 1.2 文獻回顧 1 1.2.1 結合資料庫去計算夾持位置與姿態 2 1.2.2 無資料庫的專家系統去計算夾持位置與姿態 5 1.2.3 使用機器學習的方法去計算夾持位置與姿態 9 1.3 研究動機與目的 11 1.4 論文架構 11 第二章 設計流程架構與影像處理 13 2.1 基本假設 14 2.2 通訊協定 14 2.2.1 簡單物件存取協定 14 2.2.2 傳輸控制協定 16 2.3 相機校正 19 2.4 影像處理流程 25 2.4.1 OpenCV簡介 25 2.4.2 灰階化(Grayscale) 26 2.4.3 二值化(Thresholding) 26 2.4.4 影像平滑化(Image Smoothing) 27 2.4.5 邊緣檢測(Edge Detection) 28 2.4.6 角點檢測(Corner Detection) 30 第三章 夾持點規劃 33 3.1 二指夾持點規劃原理 33 3.2 二指夾持點規劃流程 34 第四章 模擬軟體測試 44 4.1 Vrep簡介與環境架構 46 4.2 測試流程 47 4.3 可夾持範例 49 4.3.1 四邊形 49 4.3.2 五邊形 53 4.3.3 六邊形 54 4.3.4 凹多邊形 55 4.4 不可夾持範例 59 4.5 測試結果與討論 62 第五章 實際上機測試 63 5.1 系統架構 63 5.2 使用者介面 64 5.3 測試流程 66 5.4 可夾持範例 69 5.4.1 四邊形 69 5.4.2 五邊形 72 5.4.3 六邊形 73 5.4.4 凹多邊形 74 5.5 不可夾持範例 78 5.6 測試結果與討論 79 第六章 結論與未來展望 80 6.1 結論 80 6.2 未來展望 80 參考文獻 82 | |
| dc.language.iso | zh-TW | |
| dc.subject | 自動夾取流程 | zh_TW |
| dc.subject | 影像處理 | zh_TW |
| dc.subject | 角點檢測 | zh_TW |
| dc.subject | 夾持點規劃 | zh_TW |
| dc.subject | 機械手臂 | zh_TW |
| dc.subject | Automatic Grasping Pipeline | en |
| dc.subject | Image Processing | en |
| dc.subject | Corner Detection | en |
| dc.subject | Gripping Points Planning | en |
| dc.subject | Robotic Arm | en |
| dc.title | 角柱形物體之夾持點設計與夾取流程建立 | zh_TW |
| dc.title | Gripping Points Design and Grasping Pipeline Establishment for Polygonal Prisms | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 陳亮嘉(Liang-Chia Chen),廖先順(Hsien-Shun Liao) | |
| dc.subject.keyword | 自動夾取流程,影像處理,角點檢測,夾持點規劃,機械手臂, | zh_TW |
| dc.subject.keyword | Automatic Grasping Pipeline,Image Processing,Corner Detection,Gripping Points Planning,Robotic Arm, | en |
| dc.relation.page | 84 | |
| dc.identifier.doi | 10.6342/NTU201900390 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2019-02-12 | |
| 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 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-108-1.pdf 未授權公開取用 | 5.45 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。