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研究生:陳漢穎
研究生(外文):Han-Ying Chen
論文名稱:自主式水下載具利用單眼視覺之序列式蒙特卡羅定位研究
論文名稱(外文):Sequential Monte Carlo Localization for Autonomous Underwater Vehicle by Using Monocular Vision
指導教授:郭振華郭振華引用關係
指導教授(外文):Jen - Hwa Guo
口試委員:江茂雄林顯群鄭逸琳
口試委員(外文):Mao-Hsiung ChiangSheam-Chyun LinYih-Lin Cheng
口試日期:2015-06-04
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:工程科學及海洋工程學研究所
學門:工程學門
學類:綜合工程學類
論文種類:學術論文
論文出版年:2015
畢業學年度:103
語文別:中文
論文頁數:90
中文關鍵詞:自主式水下載具、水下導航、單眼視覺、序列式蒙特卡羅定位演算法
外文關鍵詞:autonomous underwater vehicleunderwater navigationmonocular visionSequential Monte Carlo Localization algorithm
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影響自主式水下載具的關鍵能力在於定位及導航。載具追蹤目標物,以及路徑控制的目的是準確辨識目標物與載具的距離和角度關係,並且透過定位結果與理想路徑的比較後可以得到較小的誤差。本文利用序列式蒙特卡羅定位演算法做為研究的方法,以水池中一組人工裝設的環境為驗證場域。首先,自主式水下載具使用單眼攝影機、電子羅盤和加速度計收集位置的量測資訊,並且建立被觀測物體與單眼視覺關係,及利用色彩空間演算法和邊緣偵測找出目標物在影像中的位置與寬度,以得到載具視訊攝影機與已知目標物間的距離及角度關係,並且整合載具的運動模型,以供自主式水下載具在已知環境下作序列式蒙特卡羅定位。最後,本文利用已知水池環境來驗證此導航法之可行性。

Localization and navigation are two crucial abilities for autonomous underwater vehicle (AUV) to track target and avoid obstacles in an underwater environment. In this work, an underwater environment was arranged for an AUV to accurately identify the relative distance and angular relationship between the AUV and the target; furthermore, the AUV was commanded to track trajectories using onboard vision. Sequential Monte Carlo localization algorithm is applied for the localization algorithm. The AUV acquires environmental and state information using a monocular camera, an electronic compass, and accelerometers for localization and navigation. While establishing the relationship between observed target and monocular camera by using image color space and edge detection to identify position, width and orientation in the reference coordinate of the target. The Sequential Monte Carlo localization in known underwater environment is then constructed by integrating vehicle motion model. The tank site was used as an example to verify the feasibility of the proposed localization and navigation method.

摘要 1
ABSTRACT II
CONTENTS III
LIST OF FIGURES VI
LIST OF TABLES IX
LIST OF SYMBOLS X
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Literature Review 2
1.3 Thesis Organization 4
Chapter 2 Hardware of the AUV 5
2.1 Hardware Introduction 5
Chapter 3 Navigation System 21
3.1 Camera Calibration 21
3.1.1 Lens Distortion Parameter Estimation 21
3.1.2 Coordinate Transformation 26
3.1.3 Camera Parameter Estimation 30
3.1.4 Distortion Adjustment 35
3.2 Image Processing 38
3.2.1 Lab Color Space 38
3.2.2 Edge Features 41
3.2.3 Hough Line Detection 43
3.3 Navigation System 45
3.3.1 Sequential Monte Carlo Localization 45
3.3.2 Motion Model 48
3.3.3 Importance Factor 52
3.3.4 Resampling 53
Chapter 4 Experimental Results 55
4.1 Test Site 55
4.2 Heading Angle and Depth Control 59
4.2.1 Heading Angle Control 60
4.2.2 Depth Control 65
4.3 Distance to Targets 68
4.3.1 Relative Position Estimate 68
4.3.2 Measurement Data Fusion 73
4.4 Localization 75
4.4.1 Extended Kalman Filter Localization 75
4.4.1.1 EKF Localization Algorithms 75
4.4.1.2 Result of EKF Localization 82
4.4.2 Result of Sequential Monte Carlo Localization 85
Chapter 5 Conclusions 87
Reference 88


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