簡易檢索 / 詳目顯示

回結果列表
研究生： 林光彥
Lin, Grant
論文名稱： 以DSP實現圖形識別於微物件操縱系統之發展
Pattern Recognition and DSP realization in micro-object manipulation
指導教授： 張仁宗
Chang, R. J.
學位類別： 碩士
Master
系所名稱： 工學院 - 機械工程學系
Department of Mechanical Engineering
論文出版年： 2005
畢業學年度： 93
語文別： 中文
論文頁數： 105
中文關鍵詞： 影像伺服 、圖形識別 、微撓性機構 、微系統操縱
外文關鍵詞： image processing, pattern recognition, visual servo, DSP, micro flexible mechanism, micro manipulation
相關次數： 點閱：77  下載：3 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

    • 　　以往以Computer-based作為影像伺服的缺點，就是在影像處理速度上的運算效率較差。故本論文以TI(德州儀器) C6000的高運算效率為基礎，搭配影像的演算法以及辨識演算法，針對程式處理效率作改善。在資料傳遞上，利用RTDX(Real-Time Data eXchange)，使DSP與PC端做即時的資料交換。

    　　另一重點在採用圖形識別(pattern recognition)之機械視覺，找出良好的處理流程，在不失物件精確度的情況下，對物件辨識動作，待辨識完成後，便進行該種物件所需的工作，搭配此一法則，更能應用於實際之情況，如生產線上的應用等等。

    　　在微系統操縱方面，以本實驗室發展多年的撓性機構微夾持器。對約70~80um的物件，進行搬運動作。

    　The shortcoming of computer-based visual servoing is inefficient on image processing. Utilizing C6000 of TI to realize the algorithms of image processing and pattern recognition, and deal with efficiency to improve the performance of the program. Utilizing RTDX (Real-Time Data eXchange ) to make DSP and PC exchange data immediately.

    　Utilizing the pattern recognition to find out the good processing procedure and recognize the object successfully without losing the accuracy position of objects. After recognizing the objects, we can make different operations according different objects. Expect that this research can be applied to the actual conditions, such as producing on-line application.

    　In the micro manipulation system, I use the flexible micro gripper developed with this laboratory to transport the 70~80um objects.

    中文摘要..................................................................................................Ⅰ Abstract.....................................................................................................Ⅱ 誌謝..........................................................................................................Ⅲ 目錄..........................................................................................................Ⅳ 表目錄......................................................................................................Ⅷ 圖目錄......................................................................................................Ⅸ 符號表..................................................................................................ⅩⅤ 第一章 緒論..............................................................................................1 1-1 前言..............................................................................................1 1-2 文獻回顧......................................................................................1 1-2.1 視覺伺服領域....................................................................2 1-2.2 圖形識別領域....................................................................6 1-2.3 圖形辨識微物件操縱領域................................................9 1-3 研究目標與方法........................................................................14 第二章 影像處理與機械視覺................................................................16 2-1 影像伺服架構............................................................................16 2-1.1 動態-觀測運動.................................................................16 2-2.2 直接視覺伺服..................................................................17 2-2 影像前處理與邊緣偵測............................................................18 2-2.1 影像前處理......................................................................18 2-2.2 邊緣偵測..........................................................................23 2-3 圖形識別....................................................................................25 2-3.1 統計圖形識別..................................................................25 2-3.2 影像重建..........................................................................27 2-3.3 連接物件標記..................................................................30 2-3.4 線性分類器......................................................................32 第三章 系統與介面架構........................................................................34 3-1 TI DSP C6000與Video Daughter Card即時傳輸規劃與設定..34 3-3.1 Video Daughter Board簡介..............................................34 3-3.2 Video Daughter Board硬體架構......................................35 3-3.3 即時傳輸規劃與設定......................................................35 3-2 TI DSP與 LabVIEW RTDX即時傳輸設定與運動平台控制..40 3-2.1 RTDX介紹........................................................................40 3-2.2 RTDX即時傳輸設定........................................................41 3-2.3 RTDX與LabVIEW傳輸設定..........................................41 3-3 C6000程式最佳化......................................................................42 3-3.1 迴圈擴展..........................................................................44 3-3.2 軟體管線最佳化技術......................................................47 第四章 微物件操縱系統........................................................................49 4-1 微夾持裝置................................................................................49 4-1.1 端效器設計......................................................................49 4-1.2 端效器製造......................................................................51 4-1.3 裝置安裝..........................................................................54 4-2 微機電圖形加工........................................................................56 4-2.1 蝕刻原理..........................................................................56 4-2.2 圖形製造流程..................................................................58 4-3 運動平台....................................................................................65 4-4 影像擷取裝置............................................................................68 4-4.1 影像擷取設備..................................................................68 4-4.2 攝影機架設方案..............................................................69 4-4.3 攝影機與平台整體架設..................................................71 第五章 系統整合與測試........................................................................72 5-1 影像處理與圖形識別................................................................72 5-1.1 影像處理結果..................................................................72 5-1.2 特徵辨識之測試..............................................................75 5-2 運動與視覺................................................................................79 5-2.1 軸平行度校準..................................................................81 5-2.2 比例係數校準..................................................................84 5-3 DSP效能測試.............................................................................85 5-3.1 DMA..................................................................................85 5-3.2 程式最佳化......................................................................85 5-3.3 快速排列法與泡沫排序法效能比較..............................86 5-3.4 遞迴處理..........................................................................86 5-3.5 整體測試..........................................................................86 5-4 自動化操縱之實作....................................................................87 第六章 結論與建議................................................................................90 6-1 結論............................................................................................90 6-2 未來展望....................................................................................91 參考文獻………………………………………………………………..92 附錄A…………………………………………………………………...97 自述……………………………………………………………………105

    [1] Nicholas R. Gans and Setch A. Hutchinson, “Performance Tests for Visual Servo Control Systems, with Application to Partitioned Approaches to Visual Servo Control,” The International Journal of Robotics Research Vol. 22, No. 10-11, October-November 2003, pp. 955-981.
    [2] Shirai, Y., and Inoue, H. “Guiding a robot by visual feedback in assembling tasks,” Pattern Recognition 5:99–108, 1973.
    [3] Corke P. I., “Visual control of robot manipulators—A review.” In K. Hashimoto, ed., Visual Servoing, Robotics and Automated Systems, Vol. 7. World Scientific, Singapore, pp. 1–31, 1993.
    [4] Weiss, L. E., Sanderson, A. C., and Neuman, C. P. “Dynamic
    sensor-based control of robots with visual feedback,” IEEE Journal of Robotics and Automation 3:404–417, 1987.
    [5] Feddema, J., and Mitchell, O. “Vision-guided servoing with feature-based trajectory generation,” IEEE Transactions on Robotics and Automation 5:691–700, 1989.
    [6] Martinet, P., Gallice, J., and Khadraoui, D. “Vision based control law using 3d visual features,” In Proceedings of WAC ’96, May, Montpellier, France, Vol. 3, pp. 497–502, 1996.
    [7] Sanderson A. C. and Weiss L. E., “Image-based visual servo control using relational graph error signals,” In Proceedings of the IEEE International Conference, 1980.
    [8] Hutchinson, S., Hager, G., and Corke, P., “A tutorial on visual servo control,” IEEE Transactions on Robotics and Automation 12:651–670, 1996.
    [9] Malis E., Chaumette F. and Boudet S., “2D 1/2 visual servoing a with respect to an unknown planar object,” Workshop on New Trends in Image-based Robot Servoing, IROS’97, Page: 45-52,France, September 1997.
    [10] Malis E., Chaumette F. and Boudet S., “Positioning a coarse-calibrate camera with respect to an unknown object by 2D 1/2 visual servoing,” Proceedings of the IEEE International Conference on Robotics and Automation, Vol.2, Pages: 1352-1359, Belguim, May 1998.
    [11] Malis E., Chaumette F. and Boudet S., “2D 1/2 visual servoing,” IEEE Journal of Robotics & Automation, Vol. 15, No. 2, Pages: 238-250, Aprail 1999.
    [12] Kragic D. and Christensen H. I., “Survey on Visual Servoing for Manipulation”.
    [13] Anil K. Jain, P. W. Duin, and Jianchang Mao, “Statistical Pattern Recognition: A Review,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.22, No. 1, January 2000.
    [14] C-J. Kim, A. P. Pisano, R. S. Muller and M. G. Lim, “Polysilicon microgripper,” 4th Technical Digest, IEEE Solid-State Sensor and Actuator Workshop, Pages: 48-51, June 1990.
    [15] 曹祖英, “微細物件組裝系統之設計、分析與測試,” 國立成功大學機械工程學系碩士論文, 頁次：3-5, 中華民國八十九年六月。
    [16] 張景堯, “形狀記憶合金驅動高分子微夾持系統之發展,” 國立成功大學機械工程學系碩士論文, 頁次：1-7, 中華民國九十二年六月。
    [17] Fatikow S., Seyfried J., Fahlbusch St., Buerkle A., Schmoeckel F. and Woern H., “Flexible microrobots for micro assembly tasks”, Micromechatronics and Human Science, 2000. MHS 2000. Proceedings of 2000 International Symposium on , 22-25 Oct. 2000
    Pages:135 – 143.
    [18] Fukuda, T., Matsuno, T. and Arai, F., “Flexible Object Manipulation by Dual Manipulator System,” Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on , Volume: 2 , 24-28 April 2000 Pages:1955 - 1960 vol.2.
    [19] Seok Joo Lee, Kyunghwan Kim, Deok-Ho Kim, Jong-Oh Park, and Gwi Tae Park, “Recognition and Track 3D-Shape Micro Parts Using Multiple Vision for Micromanipulation”.
    [20] Baidyk T., Kussul E., Makeyev O., Caballero A., Ruiz L., Carrera G., Velsaco G., “Flat image recognition in process of microdevice assembly,” Pattern Recognition Letters 25 (2004) 107-118.
    [21] Ansel Y., Schmitz F., Kunz S., Gruber H. P. and Popovic G., “Development of tools for handling and assembling microcoponents,” Journal of Micromechanics and Microengineering 12, 430-437, 2002.
    [22] Arianna Menciassi, Anna Eisinberg, Ivano Izzo and Paolo Dario, “From “Macro” to “Micro” Manipulation: Models and Experiments” Scuola Superiore Sant'Anna Center for Research In Microengineering (CRIM Lab) Pisa, Italy
    [23] Klocke V. “Motion from the nanoscale world,” Microsystem Technologies 7 256-260, 2002.
    [24] 陳泰成, “微組裝系統影像伺服建模與測試,” 國立成功大學機械工程學系碩士論文, 中華民國九十一年六月。
    [25] Markus Suing, Lothar Hermes, and Joachim M. Buhmann, “A New Contour-based Approach to Object Recognition for Assembly Line Robots,” Pattern Recognition-23rd DAGM Symposium, pp. 329-336, LNCS 2191, Springer, 2001.
    [26] Luciano Nieddu, Giacomo Patrizi, “Formal methods in pattern recognition: A review,” European Journal of Operational Research
    [27] Hutchinson S., Hager G. D. and Corke P. I., “A Tutorial on Visual Servo Control,” IEEE Transaction on Robotics & Automation, Vol.12, No.5, Pages: 651-670, October 1996.
    [28] “TMS320C6000 Imaging Developer’s Kit(IDK) User’s Guide,” Texas Instruments, 2001.
    [29] “TMS320C6000 Imaging Developer’s Kit(IDK) Video Device Driver User’s Guide,” Texas Instruments, 2001.
    [30] “vDB Technical Reference Manual(Video Daughter Board C6000 EVM/DSK),” eInfochips, 2003.
    [31] “TMS320C6000 DSP/BIOS Application Programming Interface(API) Reference Guide,” Texas Instruments, 2002.
    [32] Rafael C. Gonzalez and Richard E. Woods, “Digital Image Processing,” 2nd ed. Prentice-Hall, New York, U.S.A.
    [33] M. Sonka, V. Hlavac and R. Boyle, “Image Processing, Analysis and Machine Vision,” 2nd ed., PWS, U.S.A., 1999.
    [34] 張智星, MATLAB程式設計與應用, 清蔚科技, 台北市, 民國八十九年。
    [35] 陳信宏、王逸如, 數位訊號處理的新利器TMS320C6x, 全華科技圖書股份有限公司, 台北市, 中華民國八十九年二月。
    [36] 吳賢財, 德州儀器C6000 DSP入門實務, 滄海書局, 台中市, 中華民國九十二年一月。
    [37] Rulph chasing, “DSP Application Using C and the TMS320C6x DSK,” Wiley InterScience, 2002.
    [38] Rulph chasing, “Digital Signal Processing and Application with the C6713 and C6416,” Wiley InterScience, 2005.
    [39] Naim Dahnoun, “DSP Implementation using the TMS320C6000TM DSP Platform,” Prentice Hall, 2000.
    [40] James. R. Parker, “ALGORITHMS FOR IMAGE PROCESSING AND COMPUTER VISION,” Wiley Computer Publishing, 1997.
    [41] 惠汝生, “自動量測系統-LabVIEW”, 全華科技圖書股份有限公司, 中華民國九十一年五月。

    下載圖示 校內：2006-08-02公開
    校外：2006-08-02公開
    QR CODE