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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/58653完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 郭振華 | |
| dc.contributor.author | Yan-Hung Chen | en |
| dc.contributor.author | 陳彥宏 | zh_TW |
| dc.date.accessioned | 2021-06-16T08:24:06Z | - |
| dc.date.available | 2024-01-23 | |
| dc.date.copyright | 2014-03-18 | |
| dc.date.issued | 2014 | |
| dc.date.submitted | 2014-01-23 | |
| dc.identifier.citation | [1] F. Iwaki, M. kakihara, and M. Sasaki, “Recognition of Vehicle's Location for Navigation,” Proceedings of the Vehicle Navigation and Information Systems Conference, pp.131-138,1987.
[2] Wei-Wen Kao, “Integration of GPS and Dead-Reckoning Navigation Systems.” Proceedings of the Vehicle Navigation and Information Systems Conference,pp.635-643,1991. [3] Thomas Lezniak, Richard Lewis, and Robert Mcmillen,“ A dead reckoning/map correlation system for automatic vehicle tracking,“ IEEE Transactions on Vehicular Technology, vol. VT-26, no. 1, pp.47-60,1977. [4] Michael J. Caruso,“ Applications of magnetic sensors for low cost compass systems,” Proceedings of the IEEE Position Location and Navigation Symposium, pp.177-184,2000. [5] D.Gebre-Egziabher, G.H.Elkain, J.D. Powell, and B.W.Parkinson, “A non-linear, two-step estimation algorithm for calibrating solid-state strapdown magnetometers,” Proceedings of International Conference on Integrated Navigation Systems, pp.290-297,2001. [6] Masatoshi Hoshino, Yasuhiro Gunji, Shigeru Oho, “A Kalman filter to estimate direction for automotive navigation,” Proceedings of IEEE/SICE/RSJ International Conference Multisensor Fusion and Integration for Intelligent Systems, pp.145-150,1996. [7] Jorge Lobo and Jorge Dias, “Inertial sensed ego-motion for 3d vision,” Journal of Robotic Systems, 21(1):3-12, 2004. [8] Luis Alvarez, Luis Gomez, J. Rafael Sendra, “An Algebraic Approach to Lens Distortion by Line Rectification,” Journal of Mathematical Imaging and Vision, vol.35 no.1, pp.36-50, 2009. [9] Zhengyou Zhang, “ Flexible Camera Calibration by Viewing a Plane from Unknown Orientations,” Proceedings of International Conference on Computer Vision,pp.666-673,1999. [10] Charles Loop and Zhengyou Zhang, “Computing rectifying homographies for stereo vision,” Proceedings of IEEE Conference Vision and Pattern Recognition, vol. 1,pp.125-131,1999. [11] Richard I. Hartley, “In Defense of the Eight-Point Algorithm,” Proceedings of International Conference on Computer Vision,pp.1064-1070,1995. [12] Christine Connolly and Thomas Fliess, “A study of efficiency and accuracy in the transformation from RGB to CIELAB color space,” IEEE Transactions on Image Processing,6(7), pp.1046-1052,1997. [13] J. Illingworth and J. Kittler, “A survey of the Hough transform,” Computer Vision, Graphics, and Image Processing, vol.44, pp.87-116,1988. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/58653 | - |
| dc.description.abstract | 本研究描述自主式水下載具利用雙眼視覺、電子羅盤以及加速度計在一個磁場紊亂與已知特徵物的水下環境中的定位演算法。在實驗場地由於電子羅盤會會受到環境的干擾導致航向角的誤差變化不穩定，本文利用量測磁場分量的基本性質透過幾何關係修正受干擾的航向角值。自主式水下載具可利用修正後的角度值做角度控制以穩定地搜尋水下已知特徵物，再建立雙眼視覺來觀測載具本身與已知特徵物間的相對距離與角度當作觀測資訊；另外整合修正後的航向角與加速度計的資料去預估載具的運動模型，架構出在磁場紊亂的環境下自主式水下載具的延伸型卡曼濾波器定位演算法。最後，本論文展示在兩個不同場地下的實驗數據，以驗證此方法之可行性。 | zh_TW |
| dc.description.abstract | This work describes the localization for a autonomous underwater vehicle by utilization of stereo vision camera, a digital electronic compass, an accelerometer in known underwater environment subject to magnetic perturbations. In the experimental place, the compass could be disturbed so the heading angles differences of the vehicle are changing unstably. The proposed method of compensating the magnetic components is through the geometric relationship of magnetic components to correct the disturbed heading angles, therefore, the vehicle could control angle steadily by modified headings to search the landmarks which are known in their position. Establishing the stereo vision detects the relative distance and orientation between the known landmarks and the vehicle, then combining the information from accelerometers to perform extended Kalman filter localization algorithm to achieve autonomous localization in the magnetic anomalies environment. Finally, the experimental data in two different test tanks that are subject to strong magnetic anomalies verify the effectiveness of propose method of compensating the heading errors. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T08:24:06Z (GMT). No. of bitstreams: 1 ntu-103-R00525092-1.pdf: 5383588 bytes, checksum: 736baec4008391f7fc4379320a0606fe (MD5) Previous issue date: 2014 | en |
| dc.description.tableofcontents | 致謝...................................................... I
摘要..................................................... II ABSTRACT ................................................III CONTENTS ................................................ IV LIST OF FIGURES ........................................ VII LIST OF TABLES ........................................... X LIST OF SYMBOLS ......................................... XI Chapter 1 Introduction .................................. 1 1.1 Motivation ................................................................................................... 1 1.2 Literature Review ........................................................................................ 2 1.3 Thesis Organization .................................................................................... 4 Chapter 2 Hardware of the Autonomous Underwater Vehicle ............................ 6 2.1 Introduce the Hardware ............................................................................... 6 Chapter 3 Navigation System ................................................................................ 21 3.1 Inertial Measurement Unit (IMU) Operation ............................................ 21 3.1.1 Accelerometer and Tilt Sensor................................................. 21 3.1.2 Electronic Compass ................................................................. 28 V 3.1.3 Compass Error Analysis .......................................................... 30 3.1.4 Magnetic Component Compensating ....................................... 40 3.2 Stereo Camera Calibration ........................................................................ 48 3.2.1 Lens Distortion Parameter Estimation ..................................... 48 3.2.2 Coordinate Transformation ...................................................... 53 3.2.3 Camera Parameter Estimation.................................................. 57 3.2.4 Distortion Adjustment .............................................................. 61 3.2.5 Epipolar Geometry ................................................................... 64 3.2.6 Stereo Calibration .................................................................... 69 3.2.7 Stereo Pairs Rectification ......................................................... 71 3.2.8 Lab Color Space ....................................................................... 74 3.2.9 Edge Features ........................................................................... 76 3.2.10 Hough Line Detection ............................................................ 77 3.2.11 Stereo Vision .......................................................................... 79 3.3 Navigation System .................................................................................... 82 3.3.1 The Extended Kalman Filter Localization ............................... 82 3.3.2 The Kinematic Model .............................................................. 82 3.3.3 The Measurement Model ......................................................... 85 3.3.4 The Observation Model ........................................................... 88 3.3.5 Estimation Update .................................................................... 88 Chapter 4 Experimental Result ............................................................................. 91 4.1 The result of the compensating magnetic components ............................. 92 4.2 Introduction of the Experimental Place .................................................... 95 4.3 Experiments in NTU Water Tank ............................................................. 97 4.3.1 Magnetic Circle Detected ........................................................ 97 4.3.2 Heading Angle Analyze ........................................................... 98 4.3.3 Result of Extended Kalman Filter Localization..................... 103 4.4 Experiments in The NMMST Water Tank ............................................. 105 4.4.1 Magnetic Circle Detected ...................................................... 105 4.4.2 Heading Angle Analyze ......................................................... 107 4.4.3 Result of Extended Kalman Filter Localization..................... 109 Chapter 5 Conclusion ........................................................................................... 112 Reference .................................................................................................................. 114 | |
| dc.language.iso | en | |
| dc.title | 自主式水下載具在紊亂磁場中整合電子羅盤與已知環境之視覺導航研究 | zh_TW |
| dc.title | Navigation of an Autonomous Underwater Vehicle by Electronic Compass And Stereo Vision in a Known Environment with Magnetic Anomalies | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 102-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 江茂雄,李佳翰 | |
| dc.subject.keyword | 自主式水下載具,磁場圓,補償航向角,雙眼視覺,延伸型卡曼濾波器定位演算法, | zh_TW |
| dc.subject.keyword | autonomous underwater vehicle,magnetic compass,heading angle compensation,stereo vision,EKF localization, | en |
| dc.relation.page | 116 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2014-01-23 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 工程科學及海洋工程學研究所 | zh_TW |
| 顯示於系所單位： | 工程科學及海洋工程學系 | |
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