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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 黃漢邦(Han-Pang Huang) | |
dc.contributor.author | Astra Lee Chun Hui | en |
dc.contributor.author | 黎純蕙 | zh_TW |
dc.date.accessioned | 2021-06-07T23:46:28Z | - |
dc.date.copyright | 2020-09-17 | |
dc.date.issued | 2020 | |
dc.date.submitted | 2020-08-17 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/16799 | - |
dc.description.abstract | 人形機器人的特點在於其浮體座標系能使機器人在三度空間中移動,也能達成類似人類的動作。此一動作在進行運動計畫與控制時,需要使用完善的數學模型,在建構機器人數學模型時,其動力學參數對系統數學描述準確性扮演關鍵的角色。一般來說,此一參數係透過電腦輔助設軟體 (CAD) 設計機器人的實體模型後提供。然而,由於未建模的零件(例如電纜,螺釘和注油),使給定的參數並不完全正確,從而導致不預期與不穩定的運動問題。本文通過提出一個二次規劃的回歸模型,克服了現有不真實參數的局限性。為了克服人形機器人的穩定性,本文也提出 Single Support Motion (單腳支撐動作)方法使人形機器人在達到穩定性的情況下同時給予不同特性之軌跡進行系統識別。首先識別系統類型並考慮物理一致性條件,其次運用物體的幾何近似來設計另一組約束條件。利用所設計之約束條件使得二次規劃運可以獲得新的識別參數。此一新參數在模擬平台 (MSC ADAMS) 和人形機器人 NINO 上進行了測試。結果顯示本文所提出的方法適用於識別人形機器人系統。 | zh_TW |
dc.description.abstract | A humanoid robot is an extensive robot protocol from the conventional robot arm, its flexibility on moving in three-dimensional space allows robots to have natural movements like human beings. Locomotion and planning and control require a well-formulated mathematical model of robots for the implementation of studies. Generally, a robot is initially designed via computer-aided software to obtain the object’s parameters. However, the given parameters are not entirely true due to those unmodelled parts such as cable, screws, and oiling; therefore, the imprecise parameters lead to the inaccurate mathematical model and cause undesirable motions and serious stability problems. System identification (SI) is needed and physical conditions are crucial for the guarantee of the solutions’ feasibility. The constraints are designed based on the geometric approximation of link objects. This thesis overcomes the limitations in extant unsure parameters by proposing a quadratic programming regression model accompanied by physical consistency constraints with designated excitation motion. The proposed model considers the physical conditions and design constraints generated by the geometric approximation of link objects. In order to maintain the stability of humanoid robots, the single support motion method is proposed, this method is aimed to generate exciting trajectories where the robot is under stable situations. The identified parameters were tested in the simulation platform (MSC ADAMS software) and on a humanoid robot—NINO, proven to be feasible. | en |
dc.description.provenance | Made available in DSpace on 2021-06-07T23:46:28Z (GMT). No. of bitstreams: 1 U0001-1008202010280700.pdf: 22452805 bytes, checksum: 640871c2090c779030b9e8b15e898474 (MD5) Previous issue date: 2020 | en |
dc.description.tableofcontents | 中文口試委員會審定書 i 英文口試委員會審定書 ii 誌謝 iii 摘要 v Abstract vii List of Tables xiii List of Figures xvi Nomenclature xxiii Chapter 1 Introduction 1 1.1 Motivations 1 1.2 Contributions 3 1.3 Organization 4 Chapter 2 Literature Review 7 2.1 Machine Learning Based SI 7 2.2 Optimal Exciting Trajectory Based SI 9 2.3 Force-Sensor Based SI 9 2.3.1 Fixed-Base Robot Systems 10 2.3.2 Floating-Base Robot Systems 11 2.4 Summary 12 Chapter 3 Humanoid Robot Systems 13 3.1 Kinematics of Floating Base System 14 3.1.1 Individual Link Configuration 18 3.2 Floating-Base System Kinematic Chain 19 3.3 Dynamics of Floating-Base System 22 3.3.1 Inverse Dynamics 24 3.3.2 Forward Dynamics 26 Chapter 4 Dynamic Parameters 29 4.1 Base Dynamic Parameters 30 4.1.1 QR Decomposition 30 4.1.2 Singular Value Decomposition (SVD) 31 4.1.3 Composition Matrix Transformation 31 4.2 Essential Dynamic Parameters 32 4.3 Dynamic Parameters from CAD 33 Chapter 5 Regression Architecture 35 5.1 Regressor 35 5.2 Individual Regressor 37 5.3 Base Parameters and Base-Link Equations 38 5.4 Identifiability of Base-Link Dynamics Equations 41 5.4.1 Base-Link Regressor Composition Matrices 41 5.5 Base Parameters and Actuator-Link Equations 43 5.6 Identifiability of Full Dynamics Equations 45 5.6.1 Full Regressor Composition Matrices 45 5.7 Identifiability 46 5.8 Excitation Trajectory Generation 46 Chapter 6 Quadratic Programming Formulation 49 6.1 Quadratic Programming 49 6.1.1 Physical Consistency Constraints for QP 51 6.2 Object Geometry Inequality Constraints 54 6.3 Pre-acquisition of Dynamic Parameters 57 6.4 Design of Weight Matrix 60 6.5 Cost Evaluation 63 Chapter 7 Simulations and Experiments 65 7.1 Dynamics Simulation Environment 65 7.2 Specification of the NTU Humanoid Robot—NINO 65 7.3 Experiment Scenarios 66 7.3.1 General Walking Motion 68 7.4 Single Leg Support Motion 71 7.4.1 Left Leg Single Support (LLS) 71 7.4.2 Right Leg Single Support (RLS) 75 7.5 Results and Discussions 79 7.5.1 Condition Number Analysis 79 7.5.2 ZMP trajectories 79 Chapter 8 Conclusions and FutureWorks 89 8.1 Conclusions 89 8.2 Future Works 89 Appendices 91 A Humanoid Robot Specification: NINO 91 A.1 NINO DH Frames 91 A.2 NINO DH Table 92 A.3 NINO Dynamic Parameters from CAD, CAD 93 A.4 NINO Joint Limit 103 B Matrix Operations 104 C Coordinate Transformations 104 D Exciting Trajectories: Velocities and Accelerations 106 D.1 LSP experiment: Right leg swing back 106 D.2 LSP experiment: Right leg swing to front 107 D.3 RSP experiment: Left leg swing to side 108 D.4 RSP experiment: Left leg swing back 109 References 111 | |
dc.language.iso | en | |
dc.title | 人形機器人系統識別 | zh_TW |
dc.title | System Identification of Humanoid Robots | en |
dc.type | Thesis | |
dc.date.schoolyear | 108-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 程啟正(Chi-Cheng Cheng),蔡清元(Tsing-Iuan Tsay),李祖聖(Tzuu Hseng S. Li) | |
dc.subject.keyword | 浮體座標系,人形機器人,系統識別,二次規劃,物理一致性,單腳支撐動作, | zh_TW |
dc.subject.keyword | Floating-base system,humanoid robot,system identification,quadratic programming,physical consistency,single support motion, | en |
dc.relation.page | 115 | |
dc.identifier.doi | 10.6342/NTU202002768 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2020-08-18 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 機械工程學研究所 | zh_TW |
顯示於系所單位: | 機械工程學系 |
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