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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92358完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃漢邦 | zh_TW |
| dc.contributor.advisor | Han-Pang Huang | en |
| dc.contributor.author | 陳品存 | zh_TW |
| dc.contributor.author | Pin-Tsun Chen | en |
| dc.date.accessioned | 2024-03-21T16:46:55Z | - |
| dc.date.available | 2026-01-23 | - |
| dc.date.copyright | 2024-03-21 | - |
| dc.date.issued | 2024 | - |
| dc.date.submitted | 2024-01-23 | - |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/92358 | - |
| dc.description.abstract | 在機器人領域中，將具有高自由度（DoFs）的人形機器人應用於現實世界之各個場景仍然是件艱鉅的挑戰。過往的研究通常是採用條件與假設的簡化，如此雖然利於基礎的應用，但顯著地限制機器人的靈活性和適應性。為了應對現實世界的多樣性以及複雜條件，機器人必須採用不同的調整策略；不僅如此，為了保障應用的可行性，機器人在操作上的安全議題尤為必要。上述現象更加凸顯出擁有一個通用且靈活的控制框架對於現有人形機器人的操作效能與安全至關重要，亦是使其順利融入人類社會不可或缺的要素。
本文旨在提高仿生人形機器人對於人類社會之適應能力，並從中取得重大進展。主要有七項貢獻，這些貢獻進而增強了機器人的設計與功能性。首項創新是浮體運動學，使機器人得以將其基座設置在任意位置，提高了工作空間和穩定性。第二件是質心動量矩陣（Centroidal Momentum Matrix, CMM）的遞迴演算法，得以高效計算出每一機構之間的動量，該項目於運動規劃中扮演無可替代的角色。第三個為一種加速蒙特卡羅 (Monte Carlo) 分析的演算法，在降低複雜性的同時更大大減少運算時間。第四項則是機器人自碰撞避免之概念的引入，使用邊界球體和控制障避函數（Control Barrier Functions, CBFs）得以確保機器人整個運動過程之安全性。第五項貢獻乃基於CBF-二次規劃（Quadratic Programming, QP）的控制架構，並使用比例－微分（Proportional-Derivative , PD）控制法則以實現穩定行走。貢獻六則是將運動任務分類為全局任務與基礎任務，進而簡化軌跡之設計規劃和動作之復原校正。最後，本文提出一種角動量變化率之補償方法，使用力－扭矩感測器的回授，達成機器人之動態穩定。 這些貢獻提升機器人的效率、功能性和適應性，同時大大提高其融入人類社會的潛力。 | zh_TW |
| dc.description.abstract | The challenge of deploying humanoid robots with high degrees of freedom (DoFs) into real-world scenarios remains a pressing issue in the robotics community. Previous works in this field have often relied on simplified assumptions, which, while useful for basic applications, significantly limit the flexibility and adaptability of the robots. To address the diverse and complex conditions of real-world use, robots must be equipped to adopt different strategies. Additionally, concerns such as the safety of these robots cannot be overlooked. These factors underscore the need for a more general and flexible control framework, which is crucial for the operational efficacy and safety of existing humanoid robots.
This thesis presents significant advancements in the field of humanoid robotics, moving beyond these traditional limitations. It introduces innovations that enhance robot design and functionality in various ways. One such advancement is the development of floating-based kinematics, which allows robots to set their base at any arbitrary point, thereby expanding their workspace and enhancing stability. Another is the introduction of a recursive algorithm for the centroidal momentum matrix (CMM), crucial for efficient motion planning. Further advancements include an algorithm that accelerates Monte Carlo analysis, significantly reducing complexity and saving time. The thesis also proposes a novel self-collision avoidance algorithm that employs boundary spheres and control barrier functions (CBFs) to ensure safety during operations. A notable contribution is the development of a CBF-based quadratic programming (QP) based control framework that integrates a proportional-derivative (PD) control law, ensuring stable walking. The categorization of motion tasks into global and base tasks simplifies trajectory design and motion recovery, while the proposed angular momentum rate change compensation method, using force-torque sensor feedback, enhances dynamic stability. Collectively, these advancements mark a significant leap in humanoid robotics, improving the robots'' efficiency, functionality, and adaptability, and paving the way for their integration into human society. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2024-03-21T16:46:55Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2024-03-21T16:46:55Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | 中文口試委員會審定書 iii
英文口試委員會審定書 v 誌謝 vii 摘要 ix Abstract xi Contents xiii List of Tables xvii List of Figures xix Nomenclature xxiii Chapter 1 Introduction 1 1.1 Motivations 1 1.2 Contribution 3 1.3 Objectives 5 1.4 Organization 7 Chapter 2 Basis of Humanoid Robot Control System 11 2.1 Linear Quadratic State-Incremental Walking Pattern Generation 11 2.1.1 Dynamic Model of Humanoid Robots 12 2.1.2 Optimal Controller Design and ZMP/COM Pattern Generation 14 2.1.3 Walking Pattern Generator and Reference Trajectories 17 2.2 Floating-based Kinematics 19 2.3 Centroidal Momentum Matrix (CMM) 23 2.4 Robot Hand-arm System 31 2.4.1 Robot Hand-arm Forward Kinematics 31 2.4.2 Robot Hand-arm Forward Kinematics of Multiple End-Effectors 33 2.4.3 Robot Hand-arm Inverse Kinematics 34 2.4.4 Robot Hand-arm Damped Least Square (DLS) Method 34 2.5 Summary 36 Chapter 3 Control Barrier Function Whole-body Control (CBF-WBC) Framework 37 3.1 The Derivation and Historical Evolution of Control Barrier Functions (CBFs) 37 3.2 Introduction to Control Barrier Functions (CBFs) 41 3.3 Introduction to Floating-based Kinematics and Models 46 3.4 Integrated CBF-WBC QP Controller 49 3.4.1 Constraints 51 3.4.2 Objective Functions 64 3.4.3 CBF-WBC QP Formulation 70 3.5 Summary 74 Chapter 4 Simulations and Experiments 75 4.1 Humanoid Robot Platform and Simulation Environment 76 4.2 Workspace Simulations 80 4.2.1 The Influence of Arm Effect in Locomotion 80 4.2.2 Workspace Analysis Strategies 82 4.2.3 Results of Workspace Analysis 86 4.2.4 Complexity of Monte Carlo Algorithm 94 4.3 Simulations of Control Barrier Function-based Whole-body Control (CBF-WBC) Framework 95 4.3.1 Simulation 1: Comparison to the Algorithm with and without Self-collision Avoidance Constraint 96 4.3.2 Simulation 2: Dual-handed Self-collision Avoidance 99 4.3.3 Simulation 3: Balancing with X Direction Disturbance 104 4.3.4 Simulation 4: Dance to The Music Based on CBF-WBC 108 4.4 Experiments of Control Barrier Function-based Whole-body Control (CBF-WBC) Framework 113 4.4.1 Experiment 1: Balance Maintenance During Manipulation Task 115 4.4.2 Experiment 2: Sign Language Motions Based on CBFs 118 4.4.3 Experiment 3: Single-handed Self-collision Avoidance 119 4.4.4 Experiment 4: Dual-handed Self-collision Avoidance 121 4.4.5 Experiment 5: Balancing with X Direction Disturbance 124 4.4.6 Experiment 6: Dance to The Music Based on CBF-WBC 129 4.5 Summary 133 Chapter 5 Conclusions and Future Works 135 5.1 Conclusions 135 5.2 Future Works 137 References 141 Biography 153 | - |
| dc.language.iso | en | - |
| dc.subject | 人形機器人 | zh_TW |
| dc.subject | 浮體運動學 | zh_TW |
| dc.subject | 質心動量矩陣 | zh_TW |
| dc.subject | 控制障避函數 | zh_TW |
| dc.subject | 二次規劃 | zh_TW |
| dc.subject | humanoid robot | en |
| dc.subject | quadratic programming | en |
| dc.subject | control barrier function | en |
| dc.subject | centroidal momentum matrix | en |
| dc.subject | floating based kinematics | en |
| dc.title | 基於控制障避函數之人形機器人全身控制架構 | zh_TW |
| dc.title | Whole-Body Control Framework Based on Control Barrier Function for Humanoid Robots | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 112-1 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 郭重顯;程登湖;蔡清池 | zh_TW |
| dc.contributor.oralexamcommittee | Chung-Hsien Kuo;Teng-Hu Cheng;Ching-Chih Tsai | en |
| dc.subject.keyword | 人形機器人,浮體運動學,質心動量矩陣,控制障避函數,二次規劃, | zh_TW |
| dc.subject.keyword | humanoid robot,floating based kinematics,centroidal momentum matrix,control barrier function,quadratic programming, | en |
| dc.relation.page | 153 | - |
| dc.identifier.doi | 10.6342/NTU202400201 | - |
| dc.rights.note | 未授權 | - |
| dc.date.accepted | 2024-01-25 | - |
| dc.contributor.author-college | 工學院 | - |
| dc.contributor.author-dept | 機械工程學系 | - |
| 顯示於系所單位： | 機械工程學系 | |
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| ntu-112-1.pdf 未授權公開取用 | 10.9 MB | Adobe PDF |
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