請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73870完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳亮嘉(Liang-Chia Chen) | |
| dc.contributor.author | Wei-Han Wang | en |
| dc.contributor.author | 王維瀚 | zh_TW |
| dc.date.accessioned | 2021-06-17T08:12:24Z | - |
| dc.date.available | 2024-08-20 | |
| dc.date.copyright | 2019-09-09 | |
| dc.date.issued | 2019 | |
| dc.date.submitted | 2019-08-15 | |
| dc.identifier.citation | [1] COGNEX 公司網站。上網時間: 2019 年7月22日，檢自https://www.cognex.com/zh-tw/blogs/machine-vision/industry-4-0-machine-vision-smart-factories-and-the-industrial-internet-of-things
[2] FARO Scan Arm 公司網站。上網日期: 2019年7月22日，檢自 https://lawday.co.uk/services/inspection/ [3] A. Wheeler, “Fraunhofer IGD Builds an Autonomous 3D Scanning System”, Engineering Com, 2018. [4] R. Ishiyama, S. Sakamoto, J. Tajima, T. Okatani, and K. Deguchi, “Absolute phase measurements using geometric constraints between multiple cameras and projectors”, Applied Optics, vol. 46, pp. 3528-3538, Jun 2007. [5] D. Marr, and T. Poggio, “A Computational Theory of Human Stereo Vision”, Proceedings of the Royal Society of London. Series B. Biological Sciences 204(1156): 301. 1979. [6] J. Tian and X. Peng, “Three-dimensional vision from a multisensing mechanism”, Applied Optics, vol. 45, pp. 3003-3008, 2006. [7] M. Hansard, S. Lee, O. Choi, R. Horaud “Time of Flight Cameras: Principles, Methods, and Applications”, Springer, pp.95, 2012. [8] G. Heritage and A. Large, “Principles of 3D Laser Scanning”, Wiley-Blackwell, pp.21, 2009. [9] H. Dai, X. Su, “Shape measurement by digital speckle temporal sequence correlation with digital light projector”. Optical Engineering, 793-800, 2010. [10] M. Dekiff, P. Berssenbrügge, B. Kemper, C. Denz and D. Dirksen, “Three-dimensional data acquisition by digital correlation of projected speckle patterns” Applied Physics B, vol. 99, pp. 449-456, 2010. [11] E. Valero, V. Micó, Z. Zalevsky and J. García, “Depth sensing using coherence mapping”. Optics Communications, vol. 283, pp. 3122-3128, 2010. [12] C-W. Liang. Development of object edge measurement method using digital image correlation principle, PhD dissertation, National Taipei University of Technology, Taipei, 2017. [13] I. Ishii, K. Yamamoto, K. Doi and T. Tsuji, “High-speed 3D image acquisition using coded structured light projection”. Intelligent Robots and Systems, 2007. [14] K. Sato and S. Inokuchi, “Range-imaging system utilizing nematic liquid crystal mask”. IEEE Computer Society Press, pp. 657–661, 1987. [15] R. J. Valkenburg and A. M. McIvor, “Accurate 3D measurement using a structured light system”. Image Vision Comput, 99–110 , 1998. [16] J. L. Posdamer and M. D. Altschuler, “Surface measurement by space encoded projected beam systems”. Computer Graph Image Processing 18 (1), 1–17 , 1982. [17] D. Caspi, N. Kiryati and J. Shamir, “Range imaging with adaptive color structured light” IEEE Trans. Pattern Anal. Mach. Intell. 20 (5), 470–480 ,May 1998. [18] W. Krattenthaler, K. J. Mayer and H. P. Duwe, “3D-surface measurement with coded light approach”. in Proceedings of the 17th Meeting of the Austrian Association for Pattern Recognition on Image Analysis and Synthesis ,Vol. 12, pp. 103–114, 1993. [19] E. Stoykova, G. Minchev, V. Sainov, “Fringe projection with a sinusoidal phase grating”. Applied Optics, 48 , pp. 4774-4784, 2009. [20] S. Zhang, P. Huang, “High-resolution, Real-time 3D Shape Acquisition”. Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 3 , pp.28-37, 2004. [21] S. Zhang and S. T. Yau, “High-resolution, real-time 3D absolute coordinate measurement based on a phase-shifting method”. Opt Express, vol. 14, pp. 2644-9, Apr 2006. [22] P. S. Huang, “Color phase-shifting technique for three-dimensional shape measurement”, Optical Engineering, vol. 45, p. 013602, 2006. [23] J. Huo, Q. Wu and X. Zeng, “A technique of phase-shifting for 3-D measurement using spectral-transform”. Optics and Lasers in Engineering, vol. 51, pp. 1133-1137, 2013. [24] O. A. Skydan, M. J. Lalor and D. R. Burton, “Technique for phase measurement and surface reconstruction by use of colored structured light”. Applied Optics, vol. 41, pp. 6104-6117, Oct 2002. [25] J. Geng, “Structured-light 3-D surface imaging: A tutorial”. Adv. Optics Photonics, vol. 3, no. 2, pp. 128–160, 2011. [26] M. Takeda, H. Ina, S. Kobayashi, “Fourier-transform method of fringe-pattern analysis for computer-based topography and interferometry” Journal of the Optical Society of America, pp.156-160, 1982. [27] C-T. Thang. Multi-frequency Digital Fringe Projection Profilometry Using a Novel Hybrid Phase Unwrapping Strategy, Master thesis, National Taipei University of Technology, Taipei, 2018. [28] B. Curless, New Methods for Surface Reconstruction from Range Images, PhD dissertation, Computer Science Department, Stanford University, California, 1997. [29] G. Turk, M. Levoy, “Zippered Polygon Meshes from Range lmages”. Proc. SIGGRAPH, 1994. [30] B. -Q. Shi, J. Liang, “Guide to quickly build high-quality three-dimensional models with a structured light range scanner”. Appl. Opt., vol. 55, no. 36, pp. 10158-10169, 2016. [31] P. Surynková, “Surface Reconstruction”. WDS’09 Proceedings of Contributed Paper, Part I, 204-209, 2009. [32] CSDN網站。上網時間: 2018年12月1日，檢自https://blog.csdn.net/piaoxuezhong/article/details/68065170 [33] Theoretical fundament of Delaunay Triangulation。上網時間:2018年12月1日，檢自http://www.dma.fi.upm.es/personal/mabellanas/tfcs/flips/Intercambios/html/teoria/teoria_del_ing.htm [34] R. Mencl, et al., “Interpolation and Approximation of Surfaces from Three-Dimensional Scattered Data Points”. State of the Art Report, EURORAPHICS’98, 1997. [35] S. J. Chua and R. Jams, “Point signatures: a new representation for 3D object recognition”. International Journal of Computer Vision, 25(1):63-5, 1997. [36] D-C. Hoang, L-C. Chen, T-H. Nguyen, “Sub-OBB based object recognition and localization algorithm using range images”. Measurement Science and Technology, 2016. [37] P. J. Besl and N. D. McKay, “A method for registration of 3-D shapes”. IEEE Transactions on Pattern Recognition and Machine Intelligence 14, 239–256, 1992. [38] S. Rusinkiewicz and M. Levoy, “Efficient variants of the ICP algorithm. 3D Digital Imaging and Modeling”. Int. Conf. on, 0:145, 2001. [39] H. J. Park, S. Lim, J. C. Trinder, R. Turner, “Voxel-based volume modelling of individual trees using terrestrial laser scanners”. In: Proceedings of 15th Australasian Remote Sensing & Photogrammetry Conf., Alice Springs, Australia, pp. 1125–1133, 2010. [40] Point Cloud Library。上網時間2019年1月28日http://docs.pointclouds.org/trunk/group__kdtree.html [41] T-H. Nguyen. 3-D Object Recognition and Localization of Randomly Stacked Objects for Automation, PhD dissertation, National Taipei University of Technology, Taipei, 2015. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73870 | - |
| dc.description.abstract | 本研究於六軸機械手臂進行高精度之物件三維表面重建並利用形貌誤差分析驗證重建精度。利用空間姿態校正架之特殊排列的參考球定位物件在空間中的絕對位置，其定位精度取決於光學量測探頭，本研究使用國立台灣大學機械系精密量測實驗室所開發之雙相機光學量測探頭進行掃描，空間姿態校正架定位物件在空間中絕對位置的定位精度最小誤差可達0.123 mm，平均誤差為0.195 mm，並使用變異值最近點迭代法(Variants of the Iterative Closest Point)將兩鄰近之點雲精密的擬合(Registration)，可彌補定位精度不足的問題。此外利用適當之信心指數(Confidence)篩選點雲品質可降低31.4%的重建誤差，利用德勞內三角化(Delaunay triangulation)可有效的降低資料量並保留原始三維形貌特徵，相較於等量法降低資料量，可減少7.7%因為降低資料量而產生的形貌誤差。完成物件三維表面重建後，可利用形貌誤差分析驗證重建精度。誤差分析的精度取決於重建後的結果與CAD模型之間的對位誤差，以本研究為例，誤差分析的精度為5 μm。利用上述點雲處理相關的演算法並搭配空間姿態校正架可於六軸機械手臂上進行高精度之物件三維表面重建。 | zh_TW |
| dc.description.abstract | This study utilizes a six-axis robotic arm to achieve accurate three-dimensional object surface reconstruction. To position the object, this study designed the calibration target. The positioning accuracy of the calibration target depends on the optical measurement probe. This study utilizes the dual CCD optical measurement probe from National Taiwan University Precision Metrology Laboratory to reconstruct three-dimensional object surface. The minimum positioning accuracy of the calibration target is 0.156 mm and the mean positioning accuracy of the calibration target is 0.2 mm. To compensate the low positioning accuracy, this study implements the Variants of the Iterative Closest Point (ICP) algorithm to register two close point clouds fine. Furthermore, estimating the quality of point cloud by Confidence could reduce 31.4% of the reconstruction error. Comparing the unit downsampling and Delaunay triangulation downsampling, Delaunay triangulation downsampling could reduce 7.7% of the form error. Using object form error analysis could verify the object surface reconstruction accuracy. To analyze the form error, the CAD model of the object needs to be aligned with the surface reconstruction model of the object. The accuracy on the form error analysis depends on the alignment error. In this study, the accuracy on form error analysis is 5 μm. Integration between the calibration target and point cloud processing algorithm proposed by this study could achieve accurate three-dimensional object surface reconstruction using a 6-axis robotic arm. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T08:12:24Z (GMT). No. of bitstreams: 1 ntu-108-R06522706-1.pdf: 7497897 bytes, checksum: 655ccdb7c31ad3c2cfa0bdbc6921a1cd (MD5) Previous issue date: 2019 | en |
| dc.description.tableofcontents | 摘要 i
ABSTRACT iv 目錄 v 圖目錄 vii 表目錄 xii 第1章 緒論 1 1.1 研究背景 1 1.2 研究動機 3 1.3 研究目標 4 1.4 論文架構 5 第2章 文獻回顧 6 2.1 介紹 6 2.2 深度資訊重建 6 2.3 三維點雲前處理 11 2.4 粗擬合方法 17 2.5 細擬合方法 22 2.6 文獻回顧之總結 25 第3章 研究方法 26 3.1 研究架構 26 3.2 物件三維形貌誤差分析 27 3.3 點雲資料前處理 31 3.4 點雲資料擬合 50 3.5 研究方法之結論 64 第4章 系統架構及實驗結果 66 4.1 實驗系統之架構設計 66 4.2 物件三維形貌重建 69 4.3 物件形貌誤差分析 81 4.4 實驗結論 85 第5章 結論與未來展望 87 5.1 結論 87 5.2 未來展望 88 參考資料 90 | |
| dc.language.iso | zh-TW | |
| dc.subject | 物件三維表面重建 | zh_TW |
| dc.subject | 形貌誤差分析 | zh_TW |
| dc.subject | 信心指數 | zh_TW |
| dc.subject | 變化的最近點迭代法 | zh_TW |
| dc.subject | 三維擬合 | zh_TW |
| dc.subject | Variants of the iterative closest point | en |
| dc.subject | Form error analysis | en |
| dc.subject | Confidence | en |
| dc.subject | Object 3-D surface reconstruction | en |
| dc.subject | 3-D registration | en |
| dc.title | 應用機械手臂進行物件三維表面掃描、重建及形貌誤差分析 | zh_TW |
| dc.title | Three-Dimensional Object Surface Scanning Reconstruction and Form Error Analysis Using Robotic Manipulators | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 107-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 劉正良(Cheng-Liang Liu),何昭慶(Chao-Ching Ho),林志哲(Chih-Che Lin) | |
| dc.subject.keyword | 物件三維表面重建,形貌誤差分析,信心指數,變化的最近點迭代法,三維擬合, | zh_TW |
| dc.subject.keyword | Object 3-D surface reconstruction,Form error analysis,Confidence,Variants of the iterative closest point,3-D registration, | en |
| dc.relation.page | 95 | |
| dc.identifier.doi | 10.6342/NTU201901343 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2019-08-15 | |
| 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 | 7.32 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。