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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 王立昇(Li-Sheng Wang) | |
| dc.contributor.author | Li-Rong Liu | en |
| dc.contributor.author | 劉禮榮 | zh_TW |
| dc.date.accessioned | 2021-06-17T04:42:23Z | - |
| dc.date.available | 2023-08-13 | |
| dc.date.copyright | 2018-08-13 | |
| dc.date.issued | 2017 | |
| dc.date.submitted | 2018-08-05 | |
| dc.identifier.citation | [1]A. Heyden, and M. Pollefeys, “Multiple View Geometry“,in Emerging Topics in Computer Vision, pp.45-108, Prentice Hall, 2003.
[2]Zhengyou Zhang, “Camera Calibration with OneDimensional Objects“, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.26, No.7, pp.892-899,2004. [3]Z. Zhang, “Flexible Camera Calibration By Viewing a Plane From Unknown Orientations,” Proc. ICCV, pp. 666-673 [4]Juan Rada-vilela,“fuzzylite a fuzzy logic control library in C++“, www.fuzzylite.com, 2018. [5]Bradski, G.,“The OpenCV Library”,Dr. Dobb’s Journal of Software Tools,2015 [6]Alvy Ray Smith: “Color gamut transform pairs”, ACM Computer graphics, 12(3), August 1978. [7]C. Albitar, P. Graebling, C. Doignon, “Robust Structured Light Coding for 3D Reconstruction,” International Conference on Computer Vision, p.1-6.2007. [8]蔡政霖、余志成,”家用服務型機器人之同步定位與環境地圖建構”,中國機械工程學會第二十五屆全國學術研討會,2008 [9]Rafael C. Gonzalez,' Digital Image Processing (3rd Edition)',p.146. 2008 [10]Sobel, Irwin. (2014). “An Isotropic 3x3 Image Gradient Operator.” Presentation at Stanford A.I. Project 1968. [11]C. Papageorgiou, M. Oren, and T. Poggio. “A general framework for object detection”. In International Conference on Computer Vision, 1998. [12]R.Lienhart, A. Kuranov, V. Pisarevsky,“Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection”,MRL Technical Report, May 2002 [13]Paul Viola and Michael J. Jones. “Rapid Object Detection using a Boosted Cascade of Simple Features”. IEEE CVPR, 2001. [14] R.O.Duda,R.E.Hart. “Use of the Hough Transform to Detect Lines and Curves in Pictures”, CACM(15). No. 1, January 1972, pp. 11-15. [15] Tse-Ming Wu, “Design and Experiment of Pseudo-Rigid Formation,” Graduate Institute of Applied Mechanics, National Taiwan University Master Thesis, 2013. [16]R. Craig Conlter,” Implementation of the Pure Pursuit Path Tracking Algorithm”, Camegie Mellon University technical report, January 1992 [17]T. Takagi, M Sugeno “Fuzzy identification of systems and its applications to modeling and control” IEEE Transactions on Systems, Man, and Cybernetics ( Volume: SMC-15, Issue: 1, Jan.-Feb. 1985 ) Page(s): 116 – 132 [18] Jer-Wen Huang, “Development of Global Vision Positioning System for Pseudo-Rigid Formation Control,” Graduate Institute of Applied Mechanics, National Taiwan University Master Thesis, 2016. [19]Alarifi, Abdulrahman et al. “Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances .” Sensors (Basel, Switzerland) 16.5 (2016): 707. PMC. Web. 14 June 2018. [20]Gints Jekabsons et al,” An Analysis of Wi-Fi Based Indoor Positioning Accuracy”, Scientific Journal of Riga Technical University Vol 47,2011 [21]Giovanni Zanc et al” Experimental comparison of RSSI-based localization algorithms for indoor wireless sensor networks ”, REALWSN '08 Proceedings of the workshop on Real-world wireless sensor networks Pages 1-5,2008 [22] Chih-Yuan Wu,“Global Vision Positioning System based on K-means Clustering for Pseudo-rigid Formation Control” Graduate Institute of Applied Mechanics, National Taiwan University Master Thesis, 2017 [23] Redmon, Joseph and Farhadi, Ali, “YOLOv3: An Incremental Improvement”, arXiv.org, 2018. [24]林宗佑,”改良式A*演算法用於動態環境路徑規劃與避障”,國立台灣大學應用力學研究所畢業論文, 2018. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/70885 | - |
| dc.description.abstract | 本研究之主旨為提出一個基於電腦視覺的即時全域視覺定位(GVPS)系統，使其可以應用在室內載具平面運動的導航與控制，定位系統除了可以定出物體位置座標，也可以判斷物體的姿態。為達控制器回授所需，資料率必須達到至少每秒10次定位結果，而在本研究中提出的方法可用相當基礎的計算硬體達到每秒50次的定位結果。除此之外，我們將視覺定位系統與馬達編碼器作感測器融合，使定位系統更強韌穩定。 | zh_TW |
| dc.description.abstract | The purpose of this work is to develop a real-time Global Vision Positioning System which allows us to perform the navigation and control of an indoor unmanned vehicle. The developed system is capable to determine not only the location coordinates but also the attitude of a vehicle. To meet the design requirement, the data rate of the positioning should be faster than 10 data per second, while our algorithm can reach 50 data per second with basic end computational devices. Moreover, the visual positioning system is integrated with the motor encoder so that the integrated system could be more robust and effective. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T04:42:23Z (GMT). No. of bitstreams: 1 ntu-106-R05543054-1.pdf: 4281674 bytes, checksum: e9f588c900f9198f7dccaffc4d322d7e (MD5) Previous issue date: 2017 | en |
| dc.description.tableofcontents | 致謝 ii
摘要 iii Abstract iv 圖目錄 vii 表目錄 xi 第1章 緒論 1 1.1 前言與文獻回顧 1 1.2 文獻回顧 1 1.2.1 室內全域視覺定位 1 1.2.2 物體辨識演算法 2 1.3 研究內容與成果 2 1.4 論文架構 3 第2章 硬體配置與系統整合 4 2.1 硬體配置 4 2.1.1 M3006V型網路攝影機 5 2.1.2 馬達編碼器 6 2.2 系統運作流程 7 第3章 影像預處理 9 3.1 數位影像觀念 9 3.2 RGB及HSV色彩空間 10 3.3 影像之統計特性(histogram) 12 3.3.1 直方圖(histogram) 12 3.3.2 直方圖比較(histogram comparison) 15 3.4 影像畸變校正 16 第4章 物體辨識及定位 20 4.1 影像特徵抽取 20 4.1.1 捲積運算 20 4.1.2 Harr-like feature pool 23 4.2 分類器訓練(Viola-Jones Framework) 27 4.2.1 AdaBoost 27 4.2.2 Cascade Classifier 33 4.2.3 樣本收集與訓練 34 4.3 姿態判定方法 36 4.3.1 霍夫線轉換 36 第5章 控制器設計 40 5.1 載具動力模型[15] 40 5.2 路徑追蹤控制 42 5.3 模糊控制器 44 5.3.1 變數之歸屬函數 44 5.3.2 規則庫 47 5.3.3 模糊推論 49 5.4 感測器融合(Sensor Fusion) 50 5.4.1 遮蔽(occlusion)干擾 50 第6章 實驗 52 6.1 實驗架構 52 6.2 相機校正實驗 52 6.3 物體辨識定位實驗 55 6.3.1 V-J二元分類器訓練 55 6.3.2 histogram filter 輔助V-J 物體辨識 55 6.3.3 定位和姿態判定 57 6.4 載具追線實驗 59 6.4.1 相機位置回授 59 6.4.2 編碼器位置回授 62 6.4.3 相機與編碼器整合 68 6.5 載具即時避障實驗 73 第7章 結論與未來工作 79 參考文獻 80 | |
| dc.language.iso | zh-TW | |
| dc.title | 即時全域視覺定位系統於載具控制之應用 | zh_TW |
| dc.title | Real Time Global Vision Positioning System Applied in the Navigation and Control of an Unmanned Vehicle | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 卓大靖(Dah-Jing Jwo),王和盛(He-Sheng Wang),張帆人(Fan-ren Chang,) | |
| dc.subject.keyword | 全域視覺定位系統,室內載具, | zh_TW |
| dc.subject.keyword | Global Vision Positioning System,Indoor unmanned vehicle, | en |
| dc.relation.page | 81 | |
| dc.identifier.doi | 10.6342/NTU201801870 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2018-08-06 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 應用力學研究所 | zh_TW |
| 顯示於系所單位： | 應用力學研究所 | |
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