請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/90003
完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 馬劍清 | zh_TW |
dc.contributor.advisor | Chien-Ching Ma | en |
dc.contributor.author | 余鎧 | zh_TW |
dc.contributor.author | Kai Yu | en |
dc.date.accessioned | 2023-09-22T17:00:59Z | - |
dc.date.available | 2023-11-09 | - |
dc.date.copyright | 2023-09-22 | - |
dc.date.issued | 2023 | - |
dc.date.submitted | 2023-08-10 | - |
dc.identifier.citation | M. M. Frocht, Photoelasticity, vol. 1. J. Wiley, 1941.
A. J. Durelli and V. J. Parks, Moiré analysis of strain. Englewood Cliffs, Prentice-Hall, 1970. T. Kreis, Handbook of holographic interferometry: optical and digital methods. Wiley, 2005. H. W. Schreier and M. A. Sutton, “Systematic errors in digital image correlation due to undermatched subset shape functions.” Experimental Mechanics, vol. 42, pp. 303-310, 2002. J. H. Yan, M.A. Sutton , X. Deng, Z. Wei, and P. D. Zavattieri, “Mixed-mode crack growth in ductile thin-sheet materials under combined in-plane and out-of-plane loading.” International Journal of Fracture, vol. 160, pp. 169-188, 2009. W. H. Peters and W. F. Ranson. “Digital imaging techniques in experimental stress analysis.” Optical Engineering, vol. 21, no. 3, pp. 427-431, 1982. M. A. Sutton, W. J. Wolters, W. H. Peters, W. F. Ranson, and S.R. McNeill, “Determination of displacements using an improved digital correlation method.” Image and Vision Computing, vol. 1, no. 3, pp. 133-139, 1983. W. H. Peters, W. F. Ranson, M. A. Sutton, T. C. Chu, and J. Anderson, “ Application of digital correlation methods to rigid body mechanics,” Optical Engineering, vol. 22, no. 6, pp. 738-742, 1983. T. C. Chu, W. F. Ranson, and M. A. Sutton, “Applications of digital-image-correlation techniques to experimental mechanics.” Experimental Mechanics, vol. 25, no. 3, pp. 232-244, 1985. M. A. Sutton, C. Mingqi, W. H. Peters, Y. J. Chao, and S. R. McNeill, “Application of an optimized digital correlation method to planar deformation analysis,” Image and Vision Computing, vol. 4, no. 3, pp. 143-150, 1986. H. A. Bruck, S. R. McNeill, M. A. Sutton, and W. H. Peters III, “Digital image correlation using Newton-Raphson method of partial differential correction.” Experimental Mechanics, vol. 29, no. 3, pp. 261-267, 1989. H. Lu and P. D. Cary, “Deformation measurements by digital image correlation: implementation of a second-order displacement gradient.” Experimental Mechanics vol. 40, no. 4, pp. 393-400, 2000. G. Vendroux and W. G. Knauss, “Submicron deformation field measurements: Part 2. Improved digital image correlation.” Experimental Mechanics, vol. 38, no. 2, pp. 86-92, 1998. S. Baker and I. Matthews, “Equivalence and efficiency of image alignment algorithms.” 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2001, Kauai, HI, USA. S. Baker and I. Matthews, “Lucas-kanade 20 years on: A unifying framework.” International Journal of Computer Vision, vol. 56, no. 3, pp. 221-255, 2004. B. Pan, K. Li and W. Tong, “Fast, robust and accurate digital image correlation calculation without redundant computations.” Experimental Mechanics, vol. 53, no. 7, pp. 1277-1289, 2013. B. Pan, “An evaluation of convergence criteria for digital image correlation using inverse compositional Gauss–Newton algorithm.” Strain, vol. 50, no. 1, pp. 48-56, 2014. Y. Gao, T. Cheng, Y. Su, X. Xu, Y. Zhang, and Q. Zhang, “High-efficiency and high-accuracy digital image correlation for three-dimensional measurement.” Optics and Lasers in Engineering, vol. 65, pp. 73-80, 2015. B. Pan, H. Xie, and Z. Wang, “Equivalence of digital image correlation criteria for pattern matching,” Applied Optics, vol. 49, pp. 5501-5509, 2010. B. Pan, “Recent progress in digital image correlation.” Experimental Mechanics, vol. 51, no.7, pp. 1223-1235, 2011. Z. L. Kahn-Jetter and T. C. Chu, “Three-dimensional displacement measurements using digital image correlation and photogrammic analysis.” Experimental Mechanics, vol. 30, no. 1, pp. 10-16, 1990. P. F. Luo, Y. J. Chao, M. A. Sutton, and W. H. Peters III, “Accurate measurement of three-dimensional deformations in deformable and rigid bodies using computer vision.” Experimental Mechanics, vol. 33, no. 2, pp. 123-132, 1993. V. Tiwari, M. A. Sutton, S. R. McNeill, S. Xu, X. Deng, W. L. Fourney, and D. Bretall, “Application of 3D image correlation for full-field transient plate deformation measurements during blast loading.” International Journal of Impact Engineering, vol. 36, no. 6, pp. 862-874, 2009. M. N. Helfrick, C. Niezrecki, P. Avitabile, and T. Schmidt, “3D digital image correlation methods for full-field vibration measurement.” Mechanical Systems and Signal Processing, vol. 25, no. 3, pp. 917-927, 2011. C. Warren, C. Niezrecki, P. Avitabile, and P. Pingle, “Comparison of FRF measurements and mode shapes determined using optically image based, laser, and accelerometer measurements.” Mechanical Systems and Signal Processing, vol. 25, no. 6, pp. 2191-2202, 2011. W. Wang, J. E. Mottershead, T. Siebert, and A. Pipino, “Frequency response functions of shape features from full-field vibration measurements using digital image correlation.” Mechanical Systems and Signal Processing, vol. 28, pp. 333-347, 2012. 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. C. Y. Chang and C. C. Ma, “Increasing the computational efficient of digital cross correlation by a vectorization method.” Mechanical Systems and Signal Processing, vol. 92, pp. 293-314, 2017. C. Y. Chang and C. C. Ma, “Application of Image Processing and Computer Cluster in the Development of Full-Field Measurement for Electronic Speckle Pattern Interferometry and Digital Image Correlation.” Doctoral Dissertation, Department of Mechanical Engineering, National Taiwan University, 2012. 張景媖,馬劍清,「數位影像相關法應用於跨尺度跨領域靜態及動態全域位移與應變精密量測」,碩士論文,機械工程學研究所,臺灣大學,2013。 周宛萱,馬劍清,「建構高精度數位影像相關法並應用於土木結構動態系統及奈米材料微系統的變形量測」,碩士論文,機械工程學研究所,臺灣大學,2014。 簡宸煜,馬劍清,「應用數位影像相關法於土木結構及碳纖維性質與電池表面變化之量測」,碩士論文,機械工程學研究所,臺灣大學,2015。 彭柏勳,馬劍清,「應用數位影像相關法於機械系統與土木結構之變形及動態特性量測」,碩士論文,機械工程學研究所,臺灣大學,2016。 陳亮至,馬劍清,「建構立體數位影像相關法之基礎理論並應用於結構靜態與動態三維變形精密量測」,碩士論文,機械工程學研究所,臺灣大學,2016。 王盛儀,馬劍清,「數位影像相關法於二維軌跡及變形量測和應用於建構立體形貌」,碩士論文,機械工程學研究所,臺灣大學,2018。 黃右年,馬劍清,「建立即時立體數位影像相關法於三維工程問題的動態量測」, 碩士論文,機械工程學研究所,臺灣大學,2018。 毛英澤,馬劍清,「數位影像相關法於高速主軸即時監測與機械系統動態行為及車輛追跡之跨領域量測」,碩士論文,機械工程學研究所,臺灣大學,2019。 李宇倫,馬劍清,「提升數位影像相關法的量測精度並應用於車輛追蹤與機械手臂的三維量測」,碩士論文,機械工程學研究所,臺灣大學,2020。 陳義翔,馬劍清,「優化數位影像相關法並應用於跨尺度問題的精密量測」,碩士論文,機械工程學研究所,臺灣大學,2020。 吳俊賢,馬劍清,「建立數位結構光量測系統並應用於三維形貌與變形量測和機械手臂手眼校正與取放任務」,碩士論文,機械工程學研究所,臺灣大學,2020。 李霽儒,馬劍清,「提升數位影像相關法效能並應用於跨尺度動態問題量測與機械手臂之系統整合」,碩士論文,機械工程學研究所,臺灣大學,2021。 謝佳軒,馬劍清,「數位影像相關法於精密量測與人機共工系統的整合應用」,碩士論文,機械工程學研究所,臺灣大學,2022。 Redmon, Joseph, and Anelia Angelova. "Real-time grasp detection using convolutional neural networks." 2015 IEEE international conference on robotics and automation (ICRA). IEEE, 2015. Kumra, Sulabh, Shirin Joshi, and Ferat Sahin. "Antipodal robotic grasping using generative residual convolutional neural network." 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2020. Kingma, Diederik P., and Jimmy Ba. "Adam: A method for stochastic optimization." arXiv preprint arXiv:1412.6980 (2014). Sorkine-Hornung, Olga, and Michael Rabinovich. "Least-squares rigid motion using svd." Computing 1.1 (2017): 1-5. Lenz, Ian, Honglak Lee, and Ashutosh Saxena. "Deep learning for detecting robotic grasps." The International Journal of Robotics Research 34.4-5 (2015): 705-724. Redmon, Joseph, and Anelia Angelova. "Real-time grasp detection using convolutional neural networks." 2015 IEEE international conference on robotics and automation (ICRA). IEEE, 2015. Mahler, Jeffrey, et al. "Dex-net 2.0: Deep learning to plan robust grasps with synthetic point clouds and analytic grasp metrics." arXiv preprint arXiv:1703.09312 (2017). | - |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/90003 | - |
dc.description.abstract | 數位影像相關法(Digital image correlation, DIC)是一種非接觸的全域性光學量測技術,藉由拍攝待測物體表面的追蹤特徵,量測待測物的應變、位移、速度及加速度等多個物理量,具備跨尺度與跨領域的量測優勢。本文將應用數位影像相關法於機械手臂系統的動態性能分析,首先建構新的程式架構以提升數位影像相關法的計算速度,接著以多線程的程式架構提升工業相機取像速率後,開發機械手臂的二維以及三維即時量測軟體。軟體開發完成後,本文將探討機械手臂於無人車系統上的動態性能分析,量測該系統上之機械手臂在多種運動控制下的位移、速度以及加速度,其中的運動控制種類包括慢速、快速、複雜軌跡運動、車體移動等等,透過本文所開發的量測系統,將量測結果由相機座標系轉換至機械手臂座標系,並與機械手臂編碼器回授值相互比較,觀察機械手臂在運動過程中產生的振動以及過衝情況。另外,本文因提升工業相機的取像頻率,使得分析高速運動的物體上有所突破,過往需借助高速攝影機才能對高速移動的物體進行量測,然而高速攝影機價格高昂且僅能進行二維量測,應用本文中之量測系統,可以輕易的對高速運動物體進行三維量測,可分析的物理量包括三維的位移、速度以及加速度,為測試量測系統在加速度分析上的準確度,控制機械手臂高速移動並將加速規貼附在機械手臂上,透過數位影像相關法以及加速規的量測結果,驗證本文提出的三維數位影像相關法量測系統在加速度量測上的準確性。本文最後致力於深度學習於機械手臂取放辨識的系統開發,整合機械手臂的手眼校正流程並以模型方式辨識新穎物體的適當夾取方式,增強本實驗室在取放任務上的辨識強健性 | zh_TW |
dc.description.abstract | Digital Image Correlation (DIC) is a non-contact, full-field optical measurement technique that utilizes tracking features on the surface of a test object to measure multiple physical quantities such as strain, displacement, velocity, and acceleration. Having the advantage of cross-scale and cross-disciplinary measurements. This thesis applies DIC to the dynamic performance analysis of a robotic arm system. Firstly, a new program architecture is constructed to enhance the computational speed of DIC. Then, by improving the capturing frame rate of the industrial camera using a multi-threaded program architecture, real-time measurement software for two-dimensional and three-dimensional measurements of the robotic arm is developed. After the measurement software development, this thesis analysis the dynamic performance of the robotic arm in an Automated Guided Vehicle(AGV), measuring the displacement, velocity, and acceleration of the robotic arm under various motion controls including slow speed, high speed, complex trajectory motion, and the AGV movement. Through the measurement system developed in this thesis, the measurement results are transformed from the camera coordinate system to the robotic arm base coordinate system, and then compared with the feedback values from the robotic arm encoders to observe the vibration and overshoot generated during the arm's motion. Additionally, by improving the capturing frame rate of the industrial camera, this thesis breaks through the limitations of analyzing high-speed moving objects. Previously, high-speed cameras were required for measuring high-speed moving objects, which were expensive and limited to two-dimensional measurements. With the measurement system proposed in this thesis, high-speed moving objects can be easily measured in three dimensions, including displacement, velocity, and acceleration. To test the accuracy of the measurement system in acceleration analysis, the robotic arm is controlled to move at high speed with an accelerometer attached. The results from DIC and the accelerometer are compared to verify the accuracy of the proposed three-dimensional DIC measurement system in acceleration measurement. Finally, this thesis focuses on the development of a deep learning-based system for object recognition in robotic arm grasping tasks. The integration of hand-eye calibration processes of the robotic arm and model-based recognition of novel objects' appropriate grasping methods enhances the robustness of object recognition in our laboratory's pick-and-place tasks. | en |
dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2023-09-22T17:00:59Z No. of bitstreams: 0 | en |
dc.description.provenance | Made available in DSpace on 2023-09-22T17:00:59Z (GMT). No. of bitstreams: 0 | en |
dc.description.tableofcontents | 摘要 I
Abstract III 目錄 V 表目錄 IX 圖目錄 XI 第一章 緒論 1 1.1 研究動機 1 1.2 文獻回顧 2 1.3 內容簡介 4 第二章 數位影像相關法原理與實驗儀器 7 2.1 數位影像相關法簡介 7 2.1.1 數位影像相關法簡介 7 2.1.2 時間參數 7 2.1.3 空間參數 8 2.1.4 樣板子集合與半窗格 8 2.1.5 搜尋子集合與搜尋窗格 8 2.2 數位影像相關法計算原理 9 2.2.1 二維數位影像相關法 11 2.2.2 三維數位影像相關法 12 2.3 實驗儀器介紹 16 2.3.1 棋盤格校正板 16 2.3.2 數位工業相機 16 2.3.3 工業相機鏡頭 16 2.3.4 三軸壓電式加速規 16 2.3.5 資料擷取卡 17 2.3.6 上銀機械手臂 17 2.3.7 電動夾爪 17 2.3.8 KUKA機械手臂 18 2.3.9 Intel Realsense D435i 18 第三章 提升數位影像相關法計算效能於機械手臂動態性能量測 39 3.1 以C/C++建構二維數位影像相關法量測系統 39 3.1.1 程式語言種類 39 3.1.2 精度驗證 40 3.1.3 計算速度提升 42 3.2 建立二維機械手臂量測系統 42 3.2.1 相機校正 42 3.2.2 單相機取像流程 43 3.2.3 二維機械手臂軌跡量測實驗 44 3.2.4 即時系統 45 3.3 建立三維機械手臂量測系統 46 3.3.1 相機、世界及機械手臂之座標轉換 46 3.3.2 雙相機取像流程 49 3.3.3 三維機械手臂軌跡量測實驗 50 3.3.4 即時系統 51 3.4 小結 53 第四章 機械手臂於無人搬運車系統之動態性能分析 71 4.1 實驗架設與參數設置 71 4.2 直線軌跡實驗及振動分析 73 4.2.1 慢速運動 73 4.2.2 高速運動 74 4.3 圓弧軌跡實驗及振動分析 76 4.3.1 低速運動 76 4.3.2 高速運動 78 4.4 車體移動之系統分析 80 4.5 複雜路徑實驗量測 82 4.6 小結 82 第五章 機械手臂高速量測與深度學習於取放任務 135 5.1 機械手臂高速運動性能量測 135 5.1.1 速度與加速度計算方法 136 5.1.2 X方向高速運動分析 137 5.1.3 Y方向高速運動分析 138 5.1.4 Z方向高速運動分析 140 5.1.5 重複性震動實驗 141 5.2 機械手臂取放任務 141 5.2.1 文獻回顧 142 5.2.2 手眼校正流程 142 5.2.3 訓練方法與模型架構 144 5.2.4 辨識結果與靜態夾取任務 144 5.3 小結 146 第六章 結論與未來展望 181 6.1 結論 181 6.2 未來展望 182 參考文獻 185 | - |
dc.language.iso | zh_TW | - |
dc.title | 提升數位影像相關法計算效能並應用於機械手臂三維動態性能的即時量測與系統整合 | zh_TW |
dc.title | Improving the Computation Efficiency of Digital Image Correlation and Applying it to Three-Dimensional Dynamic Measurement of Robotic Arms in Real-Time and System Integration | en |
dc.type | Thesis | - |
dc.date.schoolyear | 111-2 | - |
dc.description.degree | 碩士 | - |
dc.contributor.oralexamcommittee | 林柏廷;楊朝龍 | zh_TW |
dc.contributor.oralexamcommittee | Po-Ting Lin;Chao-Lung Yang | en |
dc.subject.keyword | 數位影像相關法,即時三維量測,機械手臂,物件取放辨識,無人搬運車, | zh_TW |
dc.subject.keyword | Digital image correlation,Real-time three-dimensional measurement,Robotic arm,Pick-and-place,Automated Guided Vehicle, | en |
dc.relation.page | 190 | - |
dc.identifier.doi | 10.6342/NTU202304064 | - |
dc.rights.note | 未授權 | - |
dc.date.accepted | 2023-08-12 | - |
dc.contributor.author-college | 工學院 | - |
dc.contributor.author-dept | 機械工程學系 | - |
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-111-2.pdf 目前未授權公開取用 | 116.52 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。