臺灣博碩士論文加值系統

本篇論文主旨在發展配備KINECT感測器與麥卡輪全方位移動平台的雙手臂人形機器人之全域定位及地圖建立技術。首先，本文採用擴張型卡爾曼濾波方法，利用數個已知位置的人工地標融合四輪全方位移動平台上的編碼器來進行全域定位。其次，採用加速強健特徵演算法偵測及匹配部份位置未知的自然影像地標，再結合擴張型卡爾曼濾波器，進行移動式雙手臂人形機器人之全域定位及地圖建立。為了執行相關的實驗，本文建立一個以KINECT視覺感測器、以SoPC實現的四輪麥卡輪全方位移動平台及具備雙手臂之類人形行動機器人系統。利用此系統進行相關的模擬和實驗，其結果驗證了本文所提出的兩個方法的精度及性能。最後，希望本文所發展的技術對智慧機器人領域的研究有所貢獻。

This thesis presents techniques for global localization and mapping of a mobile anthropomorphous two-armed robot (ATAR) with the KINECT sensor and Mecanum four-wheeled omnidirectional base. An EKF-based global localization of the mobile ATAR is presented by using several artificial landmarks with given positions and four encoders mounted on four-wheeled omnidirectional base. An EKF-based approach using SURF is proposed for global localization and mapping of the mobile ATAR based on partially unknown natural landmarks. To conduct required experimentation, this thesis constructs an experimental, mobile, anthropomorphous two-armed robotic system with two anthropomorphous dual arms, a SoPC-based controlled Mecanum four-wheeled omnidirectional base and a KINECT sensor. Several simulations and experimental results are conducted to show the accuracy and performance of both proposed methods. The proposed techniques might be of interests to professionals working in the field of intelligent robots.

誌謝辭 i
中文摘要 i
Abstract ii
List of Figures vi
List of Tables viii
List of Acronyms x
Chapter 1 Introduction 1
1.1 Introduction 1
1.2 Literature Survey 2
1.1.1 Related Work of Localization for Mobile Robots 2
1.1.2 Related Work of Localization and Mapping for Mobile Robots 3
1.3 Motivation and Objectives 3
1.4 Main contributions 4
1.5 Thesis Organization 5
Chapter 2 System Description of the Experimental Two-Armed Robot with Omnidirectional Mecanum Wheels 6
2.1 Introduction 6
2.2 Introduction to the Two Arms and Head System 9
2.2.1 Two Arms 9
2.2.2 Head System 10
2.3 Brief Description of Mechatronic Structure of the Mobile Base 11
2.3.1 Brushless Motors 12
2.3.2 Motor Driving 12
2.3.3 Mecanum Wheels 13
2.3.4 Rotary Encoder 14
2.3.5 Power Interface 15
2.4 Brief Description of the Mobile Base Controller 16
2.4.1 SoPC Architecture 16
2.4.2 System Architecture 19
2.4.3 Wire Connectors 21
2.4.4 QEP Circuitry 21
2.4.5 Signal Flow of the Mobile Base Controller 22
2.5 KINECT sensor 23
2.5.1 The PrimeSensor 25
2.5.2 KINECT Calibration 27
2.6 Concluding Remarks 28
Chapter 3 Global Localization Using Dead-Reckoning and KINECT Sensors 29
3.1 Introduction 29
3.2 Dead-Reckoning Method 29
3.2.1 Kinematics Model in the World frame 30
3.2.2 Dead-Reckoning 33
3.3 KINECT-based Detection of Artificial Landmarks 34
3.4 Pose Initialization 37
3.5 Pose Tracking 38
3.6 Simulation Results and Discussion 40
3.6.1 Simulation of the proposed pose initialization 40
3.6.2 Simulation of the proposed pose tracking 42
3.7 Experiment Results and Discussion 43
3.7.1 Experiment of the proposed landmark detection 44
3.7.2 Experiment of the proposed pose initialization 46
3.7.3 Experiment of the proposed pose tracking for the static case 49
3.8 Concluding Remarks 50
Chapter 4 KINECT-Based Global Localization and Mapping Using Natural Landmarks 51
4.1 Introduction 51
4.2 Feature Detection of Natural Landmarks 51
4.3 EKF-based Global Localization and Mapping Algorithm 55
4.4 Computer Simulations and Discussion 60
4.4.1 Simulation Environment 60
4.4.2 The Landmarks in the Simulation 62
4.4.3 The Simulation Result 64
4.5 Concluding Remarks 64
Chapter 5 Conclusions and Future Work 66
5.1 Conclusions 66
5.2 Future Work 67
References 68

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