系統識別號 U0026-1008201816171900
論文名稱(中文) 結合物件辨識方法及立體影像重建技術進行自主式水下無人載具影像導航模組之開發
論文名稱(英文) The Development of Image Navigation System for Autonomous Underwater Vehicle by Combining Object Identification Method and Stereo- Vision Reconstruction Technique
校院名稱 成功大學
系所名稱(中) 系統及船舶機電工程學系
系所名稱(英) Department of Systems and Naval Mechatronic Engineering
學年度 106
學期 2
出版年 107
研究生(中文) 陳劭宇
研究生(英文) Shao-Yu Chen
學號 P16051177
學位類別 碩士
語文別 中文
論文頁數 131頁
口試委員 指導教授-林宇銜
中文關鍵字 自主式無人水下載具  模糊控制  邊緣偵測  霍夫轉換  立體匹配 
英文關鍵字 AUV  Fuzzy control  Edge detection  Hough transform  Stereo matching 
中文摘要 本研究的主要目的著重在視覺辨識及立體影像測深技術之開發,並應用在自主式水下無人載具影像導航系統之建構。在視覺辨識技術上結合霍夫轉換法與光流演算法作為偵測動態影像之直線特徵與移動速度;在立體影像測深技術則是利用Harris角點檢測法推估目標物之距離。經由搭載於艏艙的廣角鏡頭與雙眼視覺裝置所截取的影像作為輸入源,再透過Simscape Multibody所建立的模擬環境,可控制艉艙的後驅動系統(包含水平、垂直舵板及推進器)。在待測目標物的靜態測試上,本研究於國立成功大學系統及船舶機電工程系穩定性能水槽建置待測目標物,並於空氣與水下環境中比較不同亮度、濁度下的分析結果。最後,待測目標物的動態測試結果經結合模糊控制器,也可用以輸出目標物在不同移動速度、距離下,舵板的轉動角度、角速度與推進器的即時反應。
英文摘要 The main purpose of this research is the development of visual identification, stereo matching, and fuzzy control with an imaging module applied to the construction of an AUV navigation system. For the visual identification, the Hough transform method and the optical flow algorithm are combined to detect the linear features and moving speed of the images. In the stereo matching, the triangulation method is used to estimate the distance of the target. In the static test, the target to be tested is established in the stability tank at NCKU to compare the results under different degrees of brightness and turbidity in both air and underwater environments. Finally, the dynamic test results of the object are combined with a fuzzy controller and can also be used to output the rudder and plane angles as well as the rotation speed of the propeller.
論文目次 摘要 I
圖目錄 XX
表目錄 XXIX
第一章 緒論 1
1-1 研究背景 1
1-2 研究動機與目的 2
1-3 文獻回顧 3
第二章 AUV系統模組架構 6
2-1 水下載具外型 7
2-2 影像模組 8
2-3 AUV控制系統設計 11
2-3-1 AUV運動方程式 11
2-3-2 模糊控制 13
2-4 剛體系統建立 28
第三章 影像處理 37
3-1 色彩基礎 37
3-1-1色彩模型 39
3-2直方圖處理 40
3-2-1直方圖等化 40
3-3影像分割 42
3-4 點、線和邊緣檢測 43
3-4-1邊緣檢測 43
3-5霍夫轉換 45
3-5-1 Probabilistic Hough Transform演算法 49
3-5-2 圖像特徵點 50
3-5-3 投票 52
3-6 光流法 54
3-6-1 光流估測 55
3-6-2 疊代法 56
第四章 立體視覺影像匹配 59
4-1 立體視覺理論 59
4-2 影像特徵匹配 60
4-2-1 Harris角點檢測法(Harris Corner Detector) 61
第五章 實驗結果與分析 62
5-1 實驗設備和器材 64
5-2霍夫轉換 73
5-2-1 邊緣檢測 74
5-2-2 直線偵測 87
5-3 立體視覺量測 93
5-3-1 Harris檢測 94
5-3-2距離量測 102
5-3-3 提高對比度之結果比較 106
5-3-4 不同距離下之誤差率計算 109
5-4 使用影像搭配模糊控制 112
第六章 結果與討論 122
參考文獻 123
附錄 A. 雙眼視覺實驗配置 126
A. 水槽配置 126
B. 雙視覺影像輸出 127

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