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研究生： 祁谷風
Gustavo - Ricarte
論文名稱： 整合全域路徑規劃及局部導航之移動機器人
Hybrid of Visual Global Path Planning and Intelligent Local Navigation for Autonomous Mobile Robot
指導教授： 李敏凡
Min-Fan Ricky Lee
蘇順豐
Shun-Feng Su
口試委員: 徐繼聖
Gee-Sern Hsu
學位類別： 碩士
Master
系所名稱： 電資學院 - 電機工程系
Department of Electrical Engineering
論文出版年： 2012
畢業學年度： 100
語文別： 英文
論文頁數： 64
中文關鍵詞： .
外文關鍵詞： Intelligent local navigation, visual global path planning, dynamic obstacle avoidance, visual sensing and perception
相關次數： 點閱：129  下載：12 
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    In recent years, an autonomous mobile robot is required for performing several different tasks, such as removal of hazardous mines, exploration of volcano, monitoring nuclear power plants, etc. In general, these tasks are in hazardous and populated environments. A mobile robot must be able to deal with unexpected changes in the environment and to perform complex assignments in a short period of time.
    In this work, the focus is to provide a method for a mobile robot to navigate safely in an unknown and dynamic environment. The proposed scenario is "Assistance and Rescue Disaster", where a mobile robot is used to steer through a hazardous site in search of victims, in order to provide them rescue or emergency assistance.
    The approach used is a hybrid of visual global path plan and intelligent local navigation. The path plan is obtained by using visibility graph and Dijkstra’s algorithm, and the local navigation uses fuzzy logic to control the robot's behavior.
    Experiments were done in two different sizes of mobile robots and the initial objectives were achieved. The results show that a shorter travelled distance were obtained, as well as on-time reaction to dynamic obstacles in the robot's path.
    The outcome is that the hybrid method provides a better solution than any of the methods alone, combining the efficiency of the path planning with the dynamic response of the local navigation technique.

    ABSTRACT I ACKNOWLEDGMENTS II TABLE OF CONTENTS III LIST OF FIGURES VI LIST OF TABLES VIII CHAPTER 1 INTRODUCTION 1 1.1 GLOBAL PATH-PLANNING 5 1.1.1 Approaching the problem 6 1.1.2 Lab Color Space 8 1.1.3 Visibility Graph 8 1.2 LOCAL NAVIGATION 9 1.3 INTEGRATION OF TECHNIQUES 11 CHAPTER 2 VISUAL GLOBAL PATH PLANNING AND INTELLIGENT LOCAL NAVIGATION 13 2.1 VISUAL GLOBAL PATH PLANNING 14 2.1.1 Visual Sensing and Perception 16 A) Color Segmentation 17 B) Noise Filter 18 C) Position Detection 18 2.1.2 Path Planning 19 2.1.3 Path Tracking 19 2.2 INTELLIGENT LOCAL NAVIGATION 22 2.2.1 Scenarios – Special Conditions 30 2.3 INTEGRATION OF VISUAL GLOBAL PATH PLANNING AND INTELLIGENT LOCAL NAVIGATION 36 CHAPTER 3 EXPERIMENS AND RESULTS 38 3.1 VISUAL GLOBAL PATH PLANNING EXPERIMENTS 38 3.1.1 Scenario Setup 38 3.1.2 Experiment results 38 A) Image Processing 39 B) Optional Target 40 C) Different Scenarios 41 D) Illumination Conditions 43 3.2 INTELLIGENT LOCAL NAVIGATION EXPERIMENTS 44 3.2.1 Scenario Setup 44 3.2.2 Experiment Results 45 A) Corner Navigation 45 B) Different Configuration of Mazes 49 3.3 INTEGRATION OF METHODS 50 3.3.1 Experiments Results 50 A) Wandering for a Feasible Way 51 B) Dynamic Obstacles 53 CHAPTER 4 DISCUSSION 57 4.1 DISCUSSION OF THE EXPERIMENTS RESULTS 57 4.1.1 Visual Global Path Planning Results 57 4.1.2 Intelligent Local Navigation Results 58 4.1.3 Hybrid Approach 58 CHAPTER 5 CONCLUSION 59 5.1 CONCLUSION 59 5.2 FUTURE WORK 60 REFERENCES 61 BIOGRAPHY 65

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