請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72838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 | Chen-Han Lin | en |
| dc.contributor.author | 林晨涵 | zh_TW |
| dc.date.accessioned | 2021-06-17T07:07:41Z | - |
| dc.date.available | 2023-01-27 | |
| dc.date.copyright | 2021-03-02 | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2021-01-25 | |
| dc.identifier.citation | [1] N. Aghakhani, M. Geravand, N. Shahriari, M. Vendittelli, and G. Oriolo. “Task control with remote center of motion constraint for minimally invasive robotic surgery.” In 2013 IEEE International Conference on Robotics and Automation. pp. 5807–5812, 2013. [2] C.-A. Cheng, M. Mukadam, J. Issac, S. T. Birchfield, D. Fox, B. Boots, and N. D. Ratliff. “RMPflow: A Computational Graph for Automatic Motion Policy Generation.” ArXiv, volume abs/1811.07049, 2018. [3] N. Das and M. Yip. “Learning-Based Proxy Collision Detection for Robot Motion Planning Applications.” IEEE Transactions on Robotics, volume 36, no. 4, pp. 1096–1114, 2020. [4] A. De Santis, A. Albu-Schaffer, C. Ott, B. Siciliano, and G. Hirzinger. “The skeleton algorithm for self-collision avoidance of a humanoid manipulator.” In 2007 IEEE/ASME International Conference On Advanced Intelligent Mecha- tronics. pp. 1–6, Sep. 2007. [5] B. Eldridge, K. Gruben, D. LaRose, J. Funda, S. Gomory, J. Karidis, G. McVicker, R. Taylor, and J. Anderson. “A remote center of motion robotic arm for computer assisted surgery.” Robotica, volume 14, no. 1, p. 103–109, 1996. [6] R. He, Y. Zhao, S. Yang, and S. Yang. “Kinematic-Parameter Identification for Serial-Robot Calibration Based on POE Formula.” IEEE Transactions on Robotics, volume 26, no. 3, pp. 411–423, 2010. [7] E. M. Hoffman, A. Laurenzi, L. Muratore, N. G. Tsagarakis, and D. G. Cald- well. “Multi-Priority Cartesian Impedance Control Based on Quadratic Pro- gramming Optimization.” In 2018 IEEE International Conference on Robotics and Automation (ICRA). pp. 309–315, 2018. [8] M. Kalakrishnan, S. Chitta, E. Theodorou, P. Pastor, and S. Schaal. “STOMP: Stochastic trajectory optimization for motion planning.” Proceedings - IEEE International Conference on Robotics and Automation, pp. 4569–4574, Mar. 2011. [9] O. Khatib. “A unified approach for motion and force control of robot manip- ulators: The operational space formulation.” IEEE Journal on Robotics and Automation, volume 3, no. 1, pp. 43–53, 1987. [10] C.-H. Kuo and J. S. Dai. “Robotics for Minimally Invasive Surgery: A Historical Review from the Perspective of Kinematics.” In H.-S. Yan and M. Ceccarelli, editors, International Symposium on History of Machines and Mechanisms. Springer Netherlands, Dordrecht, pp. 337–354, 2009. [11] J. Lee, N. Mansard, and J. Park. “Intermediate Desired Value Approach for Task Transition of Robots in Kinematic Control.” IEEE Transactions on Robotics, volume 28, no. 6, pp. 1260–1277, 2012. [12] A. Li, C.-A. Cheng, B. Boots, and M. Egerstedt. “Stable, Concurrent Controller Composition for Multi-Objective Robotic Tasks.” 2019 IEEE 58th Conference on Decision and Control (CDC), pp. 1144–1151, 2019. [13] S.-Y. Lo, C.-A. Cheng, and H.-P. Huang. “Virtual Impedance Control for Safe Human-Robot Interaction.” Journal of Intelligent Robotic Systems, volume 82, no. 1, pp. 3–19, 2016. [14] M. M. Marinho, B. V. Adorno, K. Harada, and M. Mitsuishi. “Active Con- straints Using Vector Field Inequalities for Surgical Robots.” 2018 IEEE Inter- national Conference on Robotics and Automation (ICRA), pp. 1–5, 2018. [15] X. Meng, N. D. Ratliff, Y. Xiang, and D. Fox. “Neural Autonomous Navigation with Riemannian Motion Policy.” 2019 International Conference on Robotics and Automation (ICRA), pp. 8860–8866, 2019. [16] C. Ott, A. Dietrich, and A. Albu-Schäffer. “”Prioritized multi-priority compli- ance control of redundant manipulators”.” Automatica, volume 53, pp. 416 – 423, 2015. [17] R. Platt, M. Abdallah, and C. Wampler. “Multiple-priority impedance control.” In 2011 IEEE International Conference on Robotics and Automation. pp. 6033– 6038, 2011. [18] N. D. Ratliff, J. Issac, and D. Kappler. “Riemannian Motion Policies.” ArXiv, volume abs/1801.02854, 2018. [19] H. Sadeghian, L. Villani, M. Keshmiri, and B. Siciliano. “Task-Space Control of Robot Manipulators With Null-Space Compliance.” IEEE Transactions on Robotics, volume 30, no. 2, pp. 493–506, 2014. [20] J. Schulman, J. Ho, A. X. Lee, I. Awwal, H. Bradlow, and P. Abbeel. “Finding Locally Optimal, Collision-Free Trajectories with Sequential Convex Optimiza- tion.” In Robotics: Science and Systems, 2013. [21] P. Y. Tao, G. Yang, Y. C. Sun, M. Tomizuka, and C. Y. Lai. “Product-of- exponential (POE) model for kinematic calibration of robots with joint compli- ance.” In 2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). pp. 496–501, 2012. [22] C. W. Warren. “Global path planning using artificial potential fields.” In Proceedings, 1989 International Conference on Robotics and Automation. pp. 316–321 vol.1, 1989. [23] M. Zucker, N. Ratliff, A. D. Dragan, M. Pivtoraiko, M. Klingensmith, C. M. Dellin, J. A. Bagnell, and S. S. Srinivasa. “CHOMP: Covariant Hamiltonian optimization for motion planning.” The International Journal of Robotics Re- search, volume 32, no. 9-10, pp. 1164–1193, 2013. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/72838 | - |
| dc.description.abstract | 面對越來越複雜和多變的環境和人機協作的需求，現在的服務型機 器人需要動態地對環境做出回應， 這本質上是一個多優先級的問題。 傳統使用雅可比的零空間的解析解和使用最佳化和約束的數值解法並 不能有效地對每個任務的優先級進行判斷從而給出最合理的結果。本論文提出一套完整的處理機器人多任務控制和規劃的方法。基於黎曼運動決策的數學工具和高效的計算圖數據結構，機器人可以快速地在每個時間點規劃出運動。另外，本文中所有對機器人的運動學的分析都基於螺旋理論和一些基本的微分幾何理論，它們為本論文的其他部分提供了扎實的基礎。 | zh_TW |
| dc.description.abstract | Facing more and more complicated and dynamic environments as well as the requirements of human-robot interaction, modern robots may need to handle multiple tasks simultaneously and react dynamically to the environment. Analytic approaches using null space of Jacobian matrix and numerical approaches using optimization with constraints failed to provide a proper solution in some cases due to the absence of the consideration of task priorities. This article aims to solve this problem. Based on the mathematical tool of Riemannian Motion Policies with an efficient computational graph, the robot can rapidly plan its motion at each time step. In addition, the kinematic analysis of robots in this thesis is based on screw theory and some basic results of differential geometry, which form the fundamental basis. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T07:07:41Z (GMT). No. of bitstreams: 1 U0001-0401202122540800.pdf: 64494930 bytes, checksum: ca167f1a51f7546e33a5dddda8489fb8 (MD5) Previous issue date: 2021 | en |
| dc.description.tableofcontents | 誌謝 iii 摘要 v Abstract vii 1 Introduction 1 1.1 Motivations 1 1.2 Contributions 3 1.3 Organizations 4 2 Robot Kinematics and Power of Exponential Formula 7 2.1 Angular Velocities 8 2.2 Exponential Coordinate Representation of Rotation 12 2.2.1 Essential Results from Linear Differential Equations Theory . 13 2.2.2 Exponential Coordinates of Rotations 15 2.3 Rigid Body Motion - Screw Theory 19 2.4 Forward Kinematics Using Product of Exponentials Formula 25 2.4.1 Screw Axes in the Base Frame 26 2.4.2 Screw Axes in the Body Frame 28 2.5 Velocity Kinematics 28 2.6 Geometric Jacobian Matrix 31 2.7 Inverse Kinematics 32 3 Introduction to Multi-priority Robot Control and Planning 35 3.1 Motion Planning Overview 35 3.1.1 Motion Planning Methods 38 3.2 Literature Review of Multi-Priority Control 40 4 RMP and RMPflow 45 4.1 Riemannian Motion Policies 45 4.1.1 Motion Policy 46 4.1.2 Riemannian Metric 46 4.1.3 Natural Form RMP 47 4.2 RMP-tree and RMP-algebra 48 4.3 RMP and Multi-priority 52 5 Geometric Dynamic System 55 5.1 Definition 55 5.2 Stability Analysis of GDS 57 5.3 Stability Analysis of RMPflow 58 5.4 Collision Avoidance 59 5.5 Goal Attractor 63 5.6 Joint Limit Avoidance 66 6 Robot Motion Policy Generation 69 6.1 Handling Robot Kinematics : Robot Control Point 72 6.2 Target Position Tracking 76 6.3 Target Orientation Tracking 77 6.4 Joint Limit Avoidance 79 6.5 Collision Avoidance 80 6.5.1 Distance to Obstacles Using Sphere Decomposition 83 6.6 Remote Center of Motion 86 6.7 Discrete Time Control 92 6.8 RMPflow vs. Potential Field in Static Planning Environments 93 6.9 Global Guiding Planner Architecture 94 7 Applications and Experiments 99 7.1 Experiment Scenario Design 99 7.2 Experiment Parameters 101 7.3 Experiment Results 101 8 Conclusions and Future Works 107 8.1 Conclusions 107 8.2 Future Works 108 Bibliography 109 | |
| dc.language.iso | en | |
| dc.title | 基於黎曼運動決策的機器人多優先級控制與規劃 | zh_TW |
| dc.title | Robot Multi-priority Control and Planning Based on Riemannian Motion Policies | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 109-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 藍兆杰(Chao-Chieh Lan),郭重顯(Chung-Hsien Kuo),林峻永(Chun-Yeon Lin) | |
| dc.subject.keyword | 機器人,運動控制,運動規劃,多優先級控制,機器人避障, | zh_TW |
| dc.subject.keyword | robot,motion control,motion planning,multi-priority control,collision avoidance, | en |
| dc.relation.page | 111 | |
| dc.identifier.doi | 10.6342/NTU202100012 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2021-01-25 | |
| 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 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| U0001-0401202122540800.pdf 目前未授權公開取用 | 62.98 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。