博碩士論文 etd-0803110-085346 詳細資訊


姓名 黃俊豪 (Chun-hao Huang) 電子信箱 M9607214@mail.ntust.edu.tw
學號 M9607214 論文著作權 作者與指導教授共同擁有
系所名稱(中) 電機工程系 系所名稱(英) Department of Electrical Engineering
學年度 / 學期 98學年度第2學期 學位 碩士 (Master)
論文名稱(中) 以SoPC為基礎之機械手臂控制器開發
論文名稱(英) Development of a SoPC Based Robotic Manipulator Controller
檔案 本電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。
論文使用權限 校內 5 年後公開、校外永不公開
論文種類 碩士論文
論文語文別 / 頁數 中文 / 60
統計 已被瀏覽 110 次,被下載 4 次
關鍵字(中)
  • 情境模式機械手臂
  • 類神經網路
  • 賈可賓矩陣
  • 贅餘自由度
  • 機械手臂
  • 關鍵字(英)
  • scenario base robot control
  • neural network
  • Jacobian approach
  • redundancy problem
  • robotic manipulator
  • 摘要(中) 本論文目的為設計一四自由度之機械手臂運動控制器,其結構用以模
    擬人類由肩膀到手肘之間關節運動特性,此四關節之角度變化可達成手腕
    之三維空間運動。由於此機械手臂以四自由度達成手臂末端點(即手腕)
    之三維空間運動,因此其具贅餘自由度之問題。傳統上,可使用賈可賓矩
    陣規劃具贅餘自由度之空間機械手臂運動問題。但於人類手臂在不同動作
    情境下(如寫字、揮手、握手等等)會有不同之運動特徵,而賈可賓矩陣
    並無法考慮到不同行為模式下之運動特徵,致使此機械手臂無法達到相似
    於人類手臂在特定動作情境下之動作特性。因此本研究提出一以類神經網
    路為基礎之手臂運動控制器,其藉由歸納出人類手臂在不同動作情境下之
    運動特徵,其以不同模式之動作特徵產生一手臂逆向運動學之輔助解,以
    使具贅餘自由度之逆向運動學得以求解,並同時使機械手臂可以達到仿人
    手臂在特定動作情境下之運動行為。在系統實現上,本研究使用系統晶片
    基礎之機械手臂控制器開發,其採用軟硬體協同設計架構,配置軟體與硬
    體核心,以達到高效能之即時運算與控制能力。最後,本文以動作擷取系
    統來驗證本機械手臂針對不同測試軌跡以及運動模式下之效能,其結果並
    與賈可賓方法比較,來驗證此一類神經網路控制之可行性。
    摘要(英) This study aims to develop a four degree-of-freedom (DOF) robotic manipulator
    which is constructed to emulate the upper limb structure of human beings. Four joint motors are designed to perform the motions of a 3-DOF shoulder joint and a 1-DOF elbow joint. The 3D spatial motions of the end-effector (i.e., wrist) can be desired in terms of controlling the joint motor angles of the proposed 4-DOF robotic manipulator; hence, such a configuration results in the redundancy problem. In general, Jacobian solutions are linear approximations of inverse kinematics problems with redundancy conditions. Form the viewpoints of upper limbs’ motions of human beings, limb motions may be characterized as different motion scenarios. The same wrist position can be generated from different limb postures, and these postures depend on different motion scenarios such as writing words, waving hands, shaking hands, etc. As a
    consequence, Jacobian solutions are difficult to realized specific limb motion
    scenarios of human beings. Therefore, this thesis proposes a supervised neural
    network based robotic manipulator control system which constructs limb motion
    characteristic models according to relative joint posture features with respect to different motion scenarios. The generated motion features are further used to provide an auxiliary condition for eliminating the redundancy problem of the inverse kinematics as well as to meet specific motion scenarios. The proposed control system is implemented based on the “System on a Programmable Chip (SoPC)” techniques, and the proposed system is developed based on hardware-software co-design approaches. By properly allocating hardware and software modules, the system performance can be improved. Finally, several trajectory tracking experiments are done in terms of the Jacobian and neural network approaches, respectively. In order to
    verify the system performance, this study employs a motion capture system to record the experiment results. Experiment results successfully demonstrated that the proposed neural network based control system performs similar motion behaviors when compared to Jacobian approaches for the same test trajectory and motion scenario.
    論文目次 中文摘要...................................................................................................I
    英文摘要..................................................................................................II
    誌謝..........................................................................................................III
    目錄............................................................IV
    第一章 緒論......................................................................................... 1
    1-1 研究背景與動機.......................................................................1
    1-2 研究目的...................................................................................2
    1-3 論文架構...................................................................................3
    第二章 文獻回顧................................................................................. 5
    2-1 人類手臂行為模式...................................................................5
    2-2 仿人類機械手臂.......................................................................7
    2-3 機械手臂控制設計...................................................................9
    2-4 系統晶片設計.........................................................................10
    第三章 相關方法與理論介紹........................................................... 13
    3-1 機械手臂座標系統.................................................................13
    3-2 微分運動學.............................................................................15
    3-3 類神經網路.............................................................................17
    3-3-1 類神經網路理論....................................................................17 
    3-3-2 倒傳遞網路............................................................................17
    第四章 手臂行為模式運動學........................................................... 21
    4-1 機械手臂正向運動學.............................................................21
    4-2 手臂行為模式控制.................................................................23
    4-2-1 動作擷取系統........................................................................24
    4-2-2 座標系轉換............................................................................25
    4-2-3 運動特徵................................................................................26
    4-2-4 類神經網路學習與收斂........................................................28
    4-3 機械手臂逆向運動學.............................................................30
    4-4 路徑規劃.................................................................................35
    第五章 控制系統開發與實作........................................................... 38
    5-1 手臂模擬程式介面開發.........................................................38
    5-2 機械手臂.................................................................................39
    5-3 手臂控制系統.........................................................................40
    第六章 模擬與實驗........................................................................... 44
    6-1 路徑規劃模擬.........................................................................44
    6-2 人類手臂行為模式模擬.........................................................45
    6-3 控制系統測試.........................................................................52
    第七章 結論與未來方向................................................................... 55 
    參考文獻 ………………………………………………………………56
    附錄…………………………………....……………………………......59
    作者簡介……………………………....……………………………......60
    參考文獻 [1] K. Akachi, K. Kaneko, N. Kanehira, S. Ota, G. Miyamori, M. Hirata, S.
    Kajita and F. Kanehiro, “Development of Humanoid Robot HRP-3P,”
    IEEE-RAS International Conference on Humanoid Robots, pp. 50 – 55,
    2005.
    [2] I. D. Campo, J. Echanobe, G. Bosque and J. M. Tarela, “Efficient
    Hardware/Software Implementation of an Adaptive Neuro-Fuzzy System,”
    IEEE Transactions on Fuzzy System, pp. 761-778, 2008.
    [3] J.J. Craig, “Introduction to Robotics: Mechanics and Control,”
    Addison-Wesley Publishing, 1989.
    [4] C. C. Cheah, C. Liu and H. C. Liaw, “Stability of Inverse Jacobian
    Control for Robot Manipulator,” IEEE International Conference on
    Control Applications, pp. 321-326, Vol.1, 2004.
    [5] H. C. Huang and C. C. Tsai, “FPGA Implementation of an Enbedded
    Robust Adaptive Controller for Autonomous Omnidirectional Mobile
    Platform,” IEEE Transactions on Industrial Electronics, pp. 1604-1616,
    2009.
    [6] M. Hiroyasu, I. Kazuko, I. Daisuke, T. Hideaki and T. Atsuo, “Design and
    Control of 9-DOFs Emotion Expression Humanoid Arm,” IEEE
    International Conference on Robotics and Automation, pp. 128-133, Vol.1,
    2004.
    [7] A. Q. Mohammed, I. Abuhadrous and H. Elaydi, “Modeling and
    Simulation of 5 DOF Educational Robot Arm,” IEEE International
    Conference on Advanced Computer Control, pp. 569-574, 2010.
    [8] J. Rosen, J.C. Perry, N. Manning, S. Burns and B. Hannaford, “The
    Human Arm Kinematics and Dynamics during Daily Activities–toward a 7
    DOF Upper Limb Powered Exoskeleton,” International Conference On
    Advanced Robotics, 2005.
    [9] D. Tsetserukou, R. Tadakuma, H. Kajimoto, N. Kawakami and S. Tachi,
    “Intelligent Variable Joint Impedance Control and Development of a New
    Whole-Sensitive Anthropomorphic Robot Arm,” IEEE International
    Symposium on Computational Intelligence in Robotic and Automation, pp.
    338-343, 2007.
    [10] M. Tabaczynski, “Jacobian Solutions to the Inverse Kinematics Problem,”
    Tufts University, Math 128 Fall 2005 Final Project.
    [11] D. E. Whitney, “Resolved motion rate control of manipulators and human
    prostheses,” IEEE Transaction of Man-Machine Systems, Vol. 10, pp.
    47-53,1969.
    [12] O. Yu, H. Aikawa, K. Shimomura, H. Kondo, A. Morishima, H.O. Lim a,
    A. kanishi, “Development ofof a New Humanoid Robot WABIAN-2 IEEE
    International Conference On Robotics and Automation, pp. 76 - 81, 2006.
    [13] 巫憲欣, 「以系統晶片發展具機器視覺之機械手臂運動控制」 ,台灣科
    技大學,碩士論文,民國95年。
    [14] 林宏達, 「擬人型機器手臂之機構設計與控制」 ,台灣大學,碩士論文,
    民國94年。
    [15] 林志哲, 「具贅餘自由度機械臂之運動規劃與追蹤控制」 ,成功大學,
    博士論文,民國86年。
    [16] 蔡忠憲, 「移動式機械臂之抓物控制設計」 ,交通大學,碩士論文,民
    國95年。
    [17] 洪敏偉, 「水下機械手臂之設計與製作」,中山大學,碩士論文,民國95年。
    [18] 蔡勝傑, 「具贅餘自由度機械手臂之循軌控制」 ,成功大學,碩士論文,
    民國95年。
    [19] 賴昱瑋, 「具力控制之仿人機械手臂開發」 ,長庚大學,碩士論文,民
    國97年。
    [20] URL:http://www.pitotech.com.tw
    指導教授/口試委員
  • 郭重顯 - 指導教授
  • 蘇順豐 - 委員
  • 鍾聖倫 - 委員
  • 繳交日期 2010-08-04


    基本檢索 | 進階查詢 | 瀏覽檢索 | 檢索歷史 | 主頁

    如有任何問題請與國立臺灣科技大學圖書館聯繫