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研究生:蔡家豪
研究生(外文):Jia-Hao Tsai
論文名稱:應用位置阻抗控制於機械手臂手掌系統對未知位置的抓取策略
論文名稱(外文):Position-based Impedance Control for the Grasping of a Robot Hand-Arm System with Position Uncertainty
指導教授:黃漢邦黃漢邦引用關係
口試日期:2017-07-14
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:機械工程學研究所
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:英文
論文頁數:85
中文關鍵詞:機械手臂機械手掌抓握阻抗控制強韌自適應控制
外文關鍵詞:Robot Hand-Arm SystemGrasping PlanningPosition-based Impedance ControlRobust Adaptive Control
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利用多指機械手掌來進行物體的抓握,是目前機器人研究中很重要的議題之一。在一般的家庭或是工廠中,所需抓取的物體可能在各個地方相去甚遠,而如何在知道大致位置下仍能準確的抓住物體就顯得頗為重要。相對機械夾爪這種單自由度的機器,多指機器人有更多的操作空間來進行較大容許誤差的抓握。因此,本論文旨在於一定的容許誤差範圍內,利用位置阻抗控制理論以及虛擬的指間彈簧,於接觸到目標物體時,透過位於手掌的陣列型觸覺感測器以及位於手腕處的六軸力規所回授的力,來改變機械手臂及手掌的原始軌跡,使其能夠抓取目標物體。在控制底層以強韌自適應控制的方式來追取軌跡,搭配上層的阻抗控制理論改變軌跡,來達成整個抓取物體的架構。
Using a multi-fingered robot hand to grasp a target is an important objective in the research of robotics. In most factories or the average family’s household, targets may be located far from each other, so the ability to grasp the target accurately in the approximate position becomes important. Compared with mechanical grippers, which only have one degree of freedom, a multi-fingered robot hand has more operation space to grasp with a higher tolerance of error. This thesis primarily focuses on using a position-based impedance control and virtual spring between robot fingers to change the original trajectory of the robot arm and hand to grasp a target based on the feedback force/torque, which can be read from a tactile array sensor on the robot hand and six-axis force/torque sensors on the wrist when contact is made with the target. The base control, which is a robust adaptive control, can track the trajectory along with the upper control, which is the impedance control, to change the trajectory to grasp the target. A grasping model was constructed to investigate these abilities.
誌謝…………………. vii
摘要 ix
Abstract xi
List of Tables xvii
List of Figures xix
Chapter 1 Introduction 1
1.1 Motivation 1
1.2 Contributions 2
1.3 Organization 2
Chapter 2 Kinematics and Dynamics 5
2.1 Introduction 5
2.2 Inverse Kinematics 5
2.2.1 Jacobian Matrix 6
2.2.2 Iteration of Inverse Kinematics 8
2.2.3 Inverse Kinematics Algorithm 9
2.3 Inverse Dynamics 10
2.3.1 The Model of the Robot Hand-Arm System 10
2.3.2 Recursive Newton-Euler Algorithm 12
2.4 Summary 16
Chapter 3 Controller Structure 17
3.1 Introduction 17
3.2 Adaptive Robust Control 18
3.2.1 The Inner Loop Controller 18
3.2.2 The Outer Loop Controller 21
3.3 Summary 25
Chapter 4 Grasping Strategy 26
4.1 Introduction 26
4.2 Position-Based Impedance Control 26
4.2.1 The Derivation of Position-Based Impedance Control 27
4.2.2 The Discretization of the Impedance Control 30
4.3 Virtual Spatial Spring on Fingers 32
4.4 Grasping Algorithm 36
4.4.1 Power Grasp and Precision Grasp 37
4.4.2 The Trajectory of the Robot Hand and Arm 39
4.4.3 Slip Detection 41
Chapter 5 Simulations 42
5.1 Simulation Environment 42
5.2 Simulation Scenarios 46
5.2.1 Robust Adaptive Control Simulation 47
5.2.2 Impedance Control Simulation 49
5.2.3 Grasping Strategy with Power Grasp Simulation 51
5.2.4 Grasping Strategy with Precision Grasp Simulation 55
Chapter 6 Experiments 60
6.1 Integration of the Hardware System 60
6.1.1 Six-DOF Robot Arm 60
6.1.2 NTU Robotic Hand VI 61
6.1.3 Sensors 64
6.2 Software System 67
6.3 Experiment Results 69
6.3.1 Shake Hand 69
6.3.2 Grasping : Power Grasp 72
6.3.3 Grasping : Precision Grasp 74
6.3.4 Close the Door 76
6.3.5 Pick and Place an Egg 78
6.4 Summary 79
Chapter 7 Conclusions and Future Works 80
7.1 Conclusions 80
7.2 Future Works 81
References 82
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