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研究生:陳金成
研究生(外文):Chin-Cheng Chen
論文名稱:雙手臂居家服務機器人之行為模式導航與任務執行
論文名稱(外文):Behavior-Based Navigation and Task Execution of a Home-Service Robot with Two Arms
指導教授:蔡清池
學位類別:碩士
校院名稱:國立中興大學
系所名稱:電機工程學系所
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:2008
畢業學年度:96
語文別:英文
論文頁數:98
中文關鍵詞:雙手臂行為
外文關鍵詞:two armsbehavior
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本論文旨在針對一機器雙手臂結合全方位運動平台的居家服務機器人,研製該機器人的物體之影像測距、雙手臂設計、行為模式導航設計及其七軸雙手臂之前向運動學和反運動學的推導與模擬。文中,雙手臂的機構設計被詳細描述以及深度影像方法被用來進行估測物體之位置與距離。為了實現居家服務機器人能在室內未知環境內能有快速的反應能力,本文提出雷射方向權重與FKCN架構設計出行為模式導航。本文建立雙手臂之七自由度空間的前向運動學模型,在已知各軸角度可計算出機械手末端的位置。基於此模型,推導出描述機械手末端的運動速度與各關節運動關係式的Jacobian矩陣來解決多冗度問題的同時,並且可以考慮限制條件如物體碰撞或關節角度限制,來得到各軸的角度。電腦模擬與全方位平台導航實驗的成效,來檢驗所提出方法之可行性與有效性。
This thesis presents methodologies and techniques for system design, object distance calculation, behavior-based navigation, forward and inverse kinematics of a home-service robot with two seven-degrees-of-freedom arms and one three-wheeled omnidirectional mobile platform. The mechanical structure of the dual arms is described as well, and depth images are employed to determine the distances between objects and a stereo vision system. A fuzzy–Kohonen clustering network (FKCN) with laser directional weights is proposed to navigate the robot, in order to have fast responses in an unknown indoor flat environment; this navigation method is then implemented and tested on the home service robot. A kinematics model of the dual arms is derived for find the resultant postures of two effectors on the two arms if all joint angles are known. To cope with the inverse kinematics of the dual-arm, a Jacobian matrix related to the motion rates of the end effectors and the rotation rates of all joints is developed to solve for the redundancy problem of the dual arms by incorporating two constraints for obstacle avoidance and joint limit constrains. Computer simulations and experimental results are conducted to verify the feasibility and efficacy of the proposed methods.
Contents

Chinese Abstract i
English Abstract ii
Contents iii
List of Figures vii
List of Tables xi
Nomenclature xii

Chapter 1 Introduction 1
1.1 Introduction 1
1.2 Survey of Related Research 2
1.3 Motivation and Objectives 3
1.4 Contributions of the Thesis 4
1.5 Organization of the Thesis 5

Chapter 2 System Design 6
2.1 Introduction 6
2.2 Kinematic Control for Omni-Directional Mobile Platform 8
2.2.1 Kinematical Model 9
2.2.2 FPGA Implementation via Stratix Edition Nios Development Board 10
2.2.3 UART Circuit 12
2.2.4 12-Bit DA Converter 12
2.3 Laser Scanner 14
2.3.1 Measurement and Data Encoding 15
2.3.2 Communication Protocol Specifications 16
2.4 Stereo Vision Camera System 17
2.5 Stereo Vision 19
2.5.1 Establishing Correspondence 20
2.5.2 Distances Calculation 20
2.5.3 Depth Image Generation 21
2.5.3.1 Preprocessing 21
2.5.3.2 Stereo Processing 23
2.5.3.3 Distances Calculation in Depth Image and Experiment Results 24
2.6 Mechanical Structure of Dual Arms 25
2.6.1 Dual Arms 25
2.6.2 Links 26
2.6.3 Specifications of the Dual Arms 29
2.7 Concluding Remarks 31

Chapter 3 Behavior-Based Navigation 32
3.1 Introduction 32
3.2 Laser Area Weight in Heuristic FKCN Network 32
3.2.1 Design of Home Service Robot with Fuzzy Control 32
3.2.2 Calculation Method of the Laser Area Weight 35
3.2.3 Fuzzy Kohonen Clustering Network (FKCN) 35
3.2.4 Heuristic FKCN Network 37
3.2.5 Cluster of the Detected Value and the Target Direction 39
3.2.6 Construction of the Rule Table 40
3.2.7 Laser Area Weights 42
3.3 Behavior-based Navigation with Laser Area Weights 42
3.3.1 Structure of Navigation System 42
3.3.2 Behavior Fusion Module and Tournament Selection Module 43
3.3.3 Design of Obstacle Avoidance Behavior 45
3.3.3.1 Fusion Weight FWo Calculation 45
3.3.3.2 Angular Velocity ωOB Calculation 46
3.3.3.3 Velocity VOB Calculation 47
3.3.4 Design of Wall Following Behavior 48
3.3.4.1 Fusion Weight FWw Calculation 48
3.3.4.2 Robot Orientation θWB Calculation 49
3.3.4.3 Angular Velocity ωWB Calculation 51
3.3.3.4 Velocity VWB Calculation 51
3.3.5 Design of Goal Seeking Behavior 52
3.3.5.1 Fusion Weight FWG Calculation 52
3.3.5.2 Angular Velocity ωGB Calculation 54
3.3.5.3 Velocity VGB Calculation 54
3.4 Simulations and Experimental Results 55
3.4.1 Simulation of the Behavior-Based Navigation 55
3.4.2 Experimental Results and Discussions 56
3.5 Concluding Remarks 58

Chapter 4 Forward and Inverse Kinematics of Dual Arms for Task Execution 59
4.1 Introduction 59
4.2 Forward Kinematics 59
4.3 Jacobian Inverse Kinematics of Dual arms for Task Execution 66
4.3.1 One-arm Jacobian Matrix 66
4.3.2 Angular Velocity for the End Effector of the Right Arm 68
4.3.3 Jacobian Inverse Kinematics 70
4.3.4 Damped Least Squares 71
4.3.5 Joint Limit Avoidance 72
4.3.6 Obstacle Avoidance 74
4.4 Simulation Results and Discussion 76
4.5 Concluding Remarks 83


Chapter 5 Conclusions and Future Work 84
5.1 Conclusions 84
5.2 Future Work 85

References 87

Appendix A.1 89

Appendix A.2 91

Appendix A.3 93

Appendix A.4 95

List of Figures
Figure 2.1 Front view of physical structure of the home service robot 7
Figure 2.2 Back view of physical structure of the home service robot 7
Figure 2.3 Information flow structure of the proposed robot 8
Figure 2.4 Physical structure of the omni-directional mobile platform 8
Figure 2.5 Geometry of the omni-directional base 9
Figure 2.6 The Stratix edition Nios development board components 11
Figure 2.7 The FPGA design for omni-directional mobile platform system 11
Figure 2.8 The composition schematics of the QEP circuit 12
Figure 2.9 Composition diagram of the UART circuit 12
Figure 2.10 The 12-bit DAC circuit. (a) Schematic diagram 13
Figure 2.11 The 12-bit DAC circuit. (b) Pin descriptions of the headers 13
Figure 2.12 Picture of the 12-bit DAC board 13
Figure 2.13 LMS URG-04LX practical picture 14
Figure 2.14 LMS URG-04LX scanning range 15
Figure 2.15 Two modes of measurement data coding 16
Figure 2.16 Communication format 16
Figure 2.17 SVCS BB2-03S2M practical picture 18
Figure 2.18 Example of matching points between stereo images 19
Figure 2.19 Image and world coordinate systems in the library 21
Figure 2.20 Flow chart of generating depth image 21
Figure 2.21 Rectified image 22
Figure 2.22 Raw input image with edge detection 23
Figure 2.23 Distances calculation of the nose of the dog in the depth image 24
Figure 2.24 Right arm of the dual-arm 27
Figure 2.25 Link 1 27
Figure 2.26 Link 3 28
Figure 2.27 Link 5 28
Figure 2.28 Link 2 29
Figure 2.29 Link 4 29
Figure 2.30 The physical size of the dual arms 30
Figure 2.31 The finished dual arms 31
Figure 3.1 Laser area weight on the robot 34
Figure 3.2 LMS scanning area 35
Figure 3.3 FKCN structure 36
Figure 3.4 Heuristic FKCN network structure 38
Figure 3.5 Target direction 40
Figure 3.6 Seven types of environments 41
Figure 3.7 Proposed Navigation structure 42
Figure 3.8 Structure of the velocity fusion module 44
Figure 3.9 Structure of the arbitrary selection module 44
Figure 3.10 Structure of the obstacle avoidance behavior for the fusion weight FWo 45
Figure 3.11 Input and output membership functions of the fusion weight 46
Figure 3.12 Structure of the obstacle avoidance behavior for the angular velocity 46
Figure 3.13 Input and output membership functions of the angular velocity ωOB 47
Figure 3.14 Structure of the obstacle avoidance behavior for the velocity 47
Figure 3.15 Input and output membership functions of the velocity VOB 48
Figure 3.16 Structure of the wall following behavior for the fusion weight 48
Figure 3.17 Input and output membership functions of the fusion weight FWw in the fuzzy logic controller 1 49
Figure 3.18 Input and output membership functions of the fusion weight FWw in the fuzzy logic controller 2 49
Figure 3.19 Structure of the wall following behavior for the robot orientation 50
Figure 3.20 Input and output membership functions of the robot orientation θWB 50
Figure 3.21 Structure of the wall following behavior for the angular velocity 51
Figure 3.22 Input and output membership functions of the angular velocity 51
Figure 3.23 Structure of the wall following behavior for the velocity 52
Figure 3.24 Input and output membership functions of the velocity VWB 52
Figure 3.25 Structure of the goal seeking behavior for the fusion weight 53
Figure 3.26 Input and output membership functions of the fusion weight FWG 53
Figure 3.27 Structure of the goal seeking behavior for the angular velocity 54
Figure 3.28 Input and output membership functions of the angular velocity ωGB 54
Figure 3.29 Structure of the goal seeking behavior for the velocity 55
Figure 3.30 Input and output membership functions of the velocity VGB 55
Figure 3.31 Simulation of the behavior-based navigation by Borland C++ builder 56
Figure 3.32 Experimental environment with three obstacles 57
Figure 3.33 Experimental results of the HSR trajectory 57
Figure 4.1 The relationship between joint and joint 60
Figure 4.2 The relationship between joint and joint for the right arm 61
Figure 4.3 End effector frame translates and rotates with respect to fixed reference frame 64
Figure 4.4 A redundant manipulator for the obstacle avoidance 74
Figure 4.5 Using objective function method to avoid an obstacle 75
Figure 4.6 Initial postures of the dual arms 77
Figure 4.7 Jacobian inverse kinematics at the 100th generation 77
Figure 4.8 Jacobian inverse kinematics at the 250th generation 78
Figure 4.9 Jacobian inverse kinematics at the 500th generation 78
Figure 4.10 Jacobian inverse kinematics at the 1000th generation 79
Figure 4.11 Jacobian inverse kinematics for two constraints at the 100th generation 80
Figure 4.12 Jacobian inverse kinematics for two constraints at the 250th generation 81
Figure 4.13 Jacobian inverse kinematics for two constraints at the 500th generation. 81
Figure 4.14 Jacobian inverse kinematics for two constraints at the 1000th generation. 82





List of Tables
Table 2.1 Specifications of the laser scanner URG-04LX 14
Table 2.2 Specifications of stereo vision camera system BB2-03S2M 18
Table 2.3 Experimental results for determining the desired object’s postion 25
Table 2.4 Specifications of the five-link dual arms 30
Table 4.1 Link parameters for the 7-link right arm 61
Table 4.2 Simulation results of the right-arm configurations 79
Table 4.3 Simulation results of the left-arm configurations 79
Table 4.4 Simulation results of the right-arm configurations with constraints 82
Table 4.5 Simulation results of the left-arm configurations with constraints 82
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