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研究生:吳承翰
研究生(外文):Chen-Han Wu
論文名稱:應用影像處理與模糊理論於自走車動態避障
論文名稱(外文):Application of Image Process and Fuzzy Theory to Dynamic Obstacle Avoidance for an Autonomous Vehicle
指導教授:莊季高
指導教授(外文):Jih-Gau Juang
學位類別:碩士
校院名稱:國立臺灣海洋大學
系所名稱:通訊與導航工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2010
畢業學年度:98
語文別:中文
論文頁數:92
中文關鍵詞:影像處理自走車動態避障模糊控制系統
外文關鍵詞:image processWMRdynamic obstacle avoidancefuzzy control system
相關次數:
  • 被引用被引用:1
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  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:1
本篇論文主要研究自走車動態避障控制,結合CCD 攝影機和室
內定位系統所提供之資訊作為模糊控制器的輸入,以這兩種感測器為
基礎,加上經過模糊控制器運算的輸出,不需要非常複雜的數學方程
式,就可以設計出一個不錯的動態避障控制器。本論文第一部分是利
用室內定位系統所給予的座標和角度,使自走車行進在預設路線上,
再以模糊理論設計模糊控制法則,使自走車經過動態避障後能及時自
我修正回預設路徑上。第二部分主要是藉由CCD 攝影機捕捉的影
像,經過影像處理去擷取出動態障礙物的座標資料,並且計算出動態
障礙物距離自走車的距離,以及判斷動態障礙物的移動方向角度,再
以模糊法則進行動態避障控制。硬體部分使用LabView 8.5 來撰寫人
機介面,將感測器資料傳回電腦運算,產生輸出轉速,藉由WiFi
(802.11b)無線網路傳遞運算數值及自走車回授信號,影像處理用C 語
言編寫程式並結合LabView 8.5 來控制自走車。經由實驗證實,本論
文所設計的動態避障控制器運行良好。
This thesis presents dynamic obstacle avoidance control of a
wheeled mobile robot (WMR). A CCD camera and a localization system
are integrated in the control scheme, which provide the inputs of the
fuzzy controller. Based on these sensors and output operation of the fuzzy
controller, an adequate dynamic obstacle avoidance controller can be
designed without complex mathematical equation. The first part of this
thesis is the use of localization system coordinates and angles to make the
WMR move on the default path, then design fuzzy control rules by fuzzy
theory, so that after the WMR avoiding dynamic obstacle, it can be
self-corrected and return to default path promptly. The second part is the
use of CCD camera to capture images and through image processing to
obtain the coordinate data from the image of a dynamic obstacle. The
distance between dynamic obstacle and the WMR, as well as the direction
of movement of the moving obstacle can be calculated. Fuzzy rules are
applied to realize dynamic obstacle avoidance control. Hardware
implementation uses LABVIEW 8.5 to realize interface between human
and machine. Command signals are transferred through WiFi (802.11b)
wireless to communicate data between the WMR and the computer.
Image processing is handled by C code and then is integrated by
LABVIEW 8.5 to control the WMR. The experiments confirm that the
proposed dynamic obstacle avoidance control scheme works properly.
Abstract(Chinese) I
Abstract(English) II
Acknowledgement (Chinese) III
Contents IV
List of Figures VII
List of Table XI
1 Introduction 1
1.1 Preface 1
1.2 Research motivation and goal 1
1.3 Literature reviews 2
1.4 Thesis contribution 3
1.5 Organization of this thesis 4
2 WMR System Setup 5
2.1 WMR system description 5
2.2 WMR body apparatus 7
2.2.1 DC motor 7
2.2.2 MDM5253 DC motor driving module 8
2.2.3 Quadrature encoder 10
2.2.4 PMS5005 sensor and motion control card 12
2.3 Dynamic equations 13
2.4 Localization system (StarGazer) 16
2.5 Camera 18
3 Dynamic Obstacle Detection by Visual Sensor 21
3.1 Color space 21
V
3.1.1 RGB color space 21
3.1.2 HSV color space 23
3.2 Binary space 26
3.3 Erode and dilate 27
3.3.1 Erode 27
3.3.2 Dilate 29
3.4 Tag dynamic obstacle 31
3.5 Distance estimation 33
4 Fuzzy Control System 37
4.1 Introduction 37
4.2 Type-1 fuzzy control system 37
4.2.1 Fuzzification 38
4.2.2 Fuzzy rule base 39
4.2.3 Inference engine 39
4.2.4 Defuzzification 40
4.3 Simplified interval type-2 fuzzy control system 40
4.3.1 Type-2 fuzzy theory 41
4.3.2 Simplified interval type-2 fuzzy theory 44
4.4 Intelligent control scheme 47
4.4.1 Straight line path following 47
4.4.2 Adjusting optimal avoiding distance and turning angle 52
4.4.3 Dynamic obstacle avoidance 54
5 Experimental Results 63
5.1 The straight line path following 63
5.2 The dynamic obstacle avoidance 67
5.2.1 Single dynamic obstacle avoidance 68
VI
5.2.1.1 Dynamic obstacle moving to the left 68
5.2.1.2 Dynamic obstacle moving to the right 71
5.2.1.3 Dynamic obstacle moving on oblique line 74
5.2.1.4 Head-on collision avoidance 77
5.2.2 Multiple dynamic obstacles avoidance 80
6 Conclusions 87
6.1 Discussion 87
6.2 Future investigation and suggestion 87
6.2.1 Control scheme 88
6.2.2 Hardware 88
References 89
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