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系統識別號 U0026-0812200911404570
論文名稱(中文) 全方向輪式機器人之建構及其利用立體視覺與超音波資訊之導航與避障
論文名稱(英文) Construction of an Omni-directional Wheeled Robot and Its Navigation and Obstacle Avoidance Using Stereo Vision and Ultrasonic Information
校院名稱 成功大學
系所名稱(中) 機械工程學系碩博士班
系所名稱(英) Department of Mechanical Engineering
學年度 93
學期 2
出版年 94
研究生(中文) 蔡寬騰
研究生(英文) Kuan-Teng Tsai
學號 n1692470
學位類別 碩士
語文別 英文
論文頁數 91頁
口試委員 指導教授-蔡清元
口試委員-黃漢邦
口試委員-蔡新源
中文關鍵字 超音波感測系統  立體視覺  全方向輪式機器人  導航與避障 
英文關鍵字 Omni-directional Wheeled Robot  Stereo Vision  Ultrasonic Ranging System  Navigation and Obstacle Avoidance 
學科別分類
中文摘要   近年來與機器人相關之研究與理論,已為許多專家學者所共同研究與發展,且廣泛的應用於娛樂、生活援助、家庭、災害救援等領域。本論文之研究主題為發展一機器人,其可利用超音波和機器視覺等技術,完成自主式導航與擬人避障行為。機器人之系統架構可分為機械結構、感測系統、控制和驅動系統。
  其中,本研究所設計之機器人移動平台,為同時兼顧機器人的穩定性以及執行擬人避障行為,採用三個全方向輪(Omni-wheel)作為機器人的主動輪。這個移動平台可於平坦環境中任意移動和旋轉。機器人的感測系統包括自行研製之超音波系統及立體視覺系統。超音波系統提供機器人環境距離資訊,立體視覺系統則用來提供機器人目標物位置資訊,機器人根據這些資訊建立格子式環境地圖。導航控制系統根據所建立之環境地圖決策出機器人最適合的前進方向,使得機器人能逼近目標物位置且不會與環境物體發生碰撞。運動控制系統則根據該前進方向,計算求得各驅動馬達所需要的轉速,並透過所設計之控制器加以控制。
  本研究已建構一全方向輪式機器人,並以實驗驗證。該機器人無論於靜態或動態之室內環境,均能自主性的導航與避障。
英文摘要  Mobile robots have been increasingly investigated by many researchers, and applied extensively in many fields, such as entertainment, life service, household chores and calamity rescue. This thesis develops a mobile robot that utilizes ultrasonic and machine vision systems to accomplish autonomous navigation and humanoid action in obstacle avoidance. The robot is composed of a mechanical stucture, a sensing system, control and drive systems.
 Notably, the mobile base is an omni-directional wheeled mobile equipped with three omni-wheels. With this design, the base not only fulfills the requirements of high stability and mobility, but also achieves the humanoid moving motion which can be independently managed in longitudinal, lateral and rotation directions. The sensing system comprises a multiple ultrasonic system developed in this study and a stereo vision system constructed in our previous work. The multiple ultrasonic system provides the environmental ranging data, while the stereo vision supplies the target information. When the environment ranging data is obtained, the grid-type environment map is built. The main control system integrates the map information and target position to determine the most appropriate magnitude and direction of mobile robot velocity. Then, the motor speeds are computed by the motion control system according to the kinematics of the omni-directional wheeled base and the desired robot velocity.
 Consequently, an omni-directional wheeled robot with numerous functions such as autonomous navigation, free traveling in the flat room ground and humanoid obstacle avoidance behavior was constructed. Finally, experiments were performed to verify the effectiveness of functions for the developed robot regardless whether the room environment is static or dynamic.
論文目次 Abstract I
Contents II
List of Tables V
List of Figures VI

1 Introduction 1
1.1 Motivations and Objective 1
1.2 Literature Survey 2
1.3 Contribution of This Thesis 3
1.4 Organization of This Thesis 4

2 System Design and Development 5
2.1 Design of Mobile Robot 5
2.2 Omni-directional Mobile Base 7
2.2.1 Mechatronics Design 7
2.2.2 Holonomic Motion Control 9
2.3 Ultrasonic Ranging System 11
2.4 Stereo Vision Head 12

3 Ultrasonic Ranging System 20
3.1 Characteristic and Limitations of Ultrasonic Sensors 20
3.2 Polaroid Ultrasonic Ranging Module 22
3.3 Design of Firing Schedule 23

4 Image Processing and Stereo Vision 28
4.1 Image Processing 28
4.1.1 Color Conversion 29
4.1.2 Blob Analysis 30
4.2 Fundamentals of Stereo Vision 30
4.2.1 Camera Model 30
4.2.2 Epipolar Geometry 32
4.3 Image Rectification 33
4.4 Stereo Matching 35
4.5 Reconstruction 37
4.6 Target Localization 38

5 Obstacle Avoidance 44
5.1 Environment Model 44
5.2 Obstacle Avoider 46
5.2.1 Creation of the Polar Histogram 48
5.2.2 Binary Polar Histogram 50
5.2.3 Selection of Steering Direction 51

6 Simulation and Experimentation 57
6.1 Motion Control of Omni-directional Wheeled Robot 57
6.1.1 Experimental Setup 58
6.1.2 Simulation Results 58
6.1.3 Experimental Results 59
6.2 Experiment for Stereo Vision 59
6.2.1 Image Rectification 59
6.2.2 Experimental Results for the Distance Measurement 61
6.3 Experiment for the Autonomous Navigation and Obstacle Avoidance 62
6.3.1 Obstacle avoidance in Static Environment 63
6.3.2 Obstacle avoidance in Dynamic Environment 64

7 Conclusions 86
7.1 Conclusions 86
7.2 Future Works 87

Reference 89
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