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  1. NTU Theses and Dissertations Repository
  2. 工學院
  3. 機械工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/94861
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor林沛群zh_TW
dc.contributor.advisorPei-Chun Linen
dc.contributor.author盧冠綸zh_TW
dc.contributor.authorKuan-Lun Luen
dc.date.accessioned2024-08-20T16:12:39Z-
dc.date.available2024-08-21-
dc.date.copyright2024-08-20-
dc.date.issued2024-
dc.date.submitted2024-08-08-
dc.identifier.citation[1] Gerardo Bledt, Matthew J. Powell, Benjamin Katz, Jared Di Carlo, Patrick M. Wensing, and Sangbae Kim. Mit cheetah 3: Design and control of a robust, dynamic quadruped robot. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 2245-2252, 2018.
[2] Marco Hutter, Christian Gehring, Dominic Jud, Andreas Lauber, C. Dario Bellicoso, Vassilios Tsounis, Jemin Hwangbo, Karen Bodie, Peter Fankhauser, Michael Bloesch, Remo Diethelm, Samuel Bachmann, Amir Melzer, and Mark Hoepflinger. Anymal - a highly mobile and dynamic quadrupedal robot. In 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 38-44, 2016.
[3] Claudio Semini. Hyq-design and development of a hydraulically actuated quadruped robot. Doctor of Philosophy (Ph. D.), University of Genoa, Italy, 2010.
[4] Marko Bjelonic, Ruben Grandia, Oliver Harley, Cla Galliard, Samuel Zimmermann, and Marco Hutter. Whole-body mpc and online gait sequence generation for wheeled-legged robots. In 2021 IEEE/RSJ international conference on intelligent robots and systems (IROS), pages 8388-8395. IEEE, 2021.
[5] Marko Bjelonic, C Dario Bellicoso, Yvain de Viragh, Dhionis Sako, F Dante Tresoldi, Fabian Jenelten, and Marco Hutter. Keep rollin’ —whole-body motion control and planning for wheeled quadrupedal robots. IEEE Robotics and Automation Letters, 4(2):2116-2123, 2019.
[6] Gen Endo and Shigeo Hirose. Study on roller-walker - energy efficiency of roller-walk -. In 2011 IEEE International Conference on Robotics and Automation, pages 5050-5055, 2011.
[7] Ruixiang Cao, Jun Gu, Chen Yu, and Andre Rosendo. Omniwheg: An omnidirectional wheel-leg transformable robot. In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 5626-5631, IEEE, 2022.
[8] Yoo-Seok Kim, Gwang-Pil Jung, Haan Kim, Kyu-Jin Cho, and Chong-Nam Chu. Wheel transformer: A wheel-leg hybrid robot with passive transformable wheels. IEEE Transactions on Robotics, 30(6):1487-1498, 2014.
[9] Zhong Wei, Guangming Song, Ying Zhang, Huiyu Sun, and Guifang Qiao. Transleg: A wire-driven leg-wheel robot with a compliant spine. In 2016 IEEE International Conference on Information and Automation (ICIA), pages 7-12, 2016.
[10] Shen-Chiang Chen, Ke-Jung Huang, Wei-Hsi Chen, Shuan-Yu Shen, Cheng-Hsin Li, and Pei-Chun Lin. Quattroped: a leg-wheel transformable robot. IEEE/ASME Transactions On Mechatronics, 19(2):730-742, 2013.
[11] Wei-Hsi Chen, Hung-Sheng Lin, Yun-Meng Lin, and Pei-Chun Lin. Turboquad: A novel leg-wheel transformable robot with smooth and fast behavioral transitions. IEEE Transactions on Robotics, 33(5):1025-1040, 2017.
[12] Shigang Wang, Kai Ma, Xu Deng, and Xianghua Liao. Quadruped robot foot-end trajectory generation algorithm. In 2022 2nd International Conference on Computation, Communication and Engineering (ICCCE), pages 114-119, IEEE, 2022.
[13] Dong Jin Hyun, Sangok Seok, Jongwoo Lee, and Sangbae Kim. High speed trot-running: Implementation of a hierarchical controller using proprioceptive impedance control on the mit cheetah. The International Journal of Robotics Research, 33(11):1417-1445, 2014.
[14] Hae-Won Park, Sangin Park, and Sangbae Kim. Variable-speed quadrupedal bounding using impulse planning: Untethered high-speed 3d running of mit cheetah 2. In 2015 IEEE International Conference on Robotics and Automation (ICRA), pages 5163-5170, 2015.
[15] Jared Di Carlo. Software and control design for the MIT Cheetah quadruped robots. PhD thesis, Massachusetts Institute of Technology, 2020.
[16] Fabian Jenelten, Takahiro Miki, Aravind E Vijayan, Marko Bjelonic, and Marco Hutter. Perceptive locomotion in rough terrain -online foothold optimization. IEEE Robotics and Automation Letters, 5(4):5370-5376, 2020.
[17] Vassilios Tsounis, Mitja Alge, Joonho Lee, Farbod Farshidian, and Marco Hutter. Deepgait: Planning and control of quadrupedal gaits using deep reinforcement learning. IEEE Robotics and Automation Letters, 5(2):3699-3706, 2020.
[18] C Dario Bellicoso, Fabian Jenelten, Péter Fankhauser, Christian Gehring, Jemin Hwangbo, and Marco Hutter. Dynamic locomotion and whole-body control for quadrupedal robots. In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 3359-3365, IEEE, 2017.
[19] Ioannis Havoutis, Jesus Ortiz, Stéphane Bazeille, Victor Barasuol, Claudio Semini, and Darwin G. Caldwell. Onboard perception-based trotting and crawling with the hydraulic quadruped robot (hyq). In 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 6052-6057, 2013.
[20] Thiago Boaventura, Gustavo A. Medrano-Cerda, Claudio Semini, Jonas Buchli, and Darwin G. Caldwell. Stability and performance of the compliance controller of the quadruped robot hyq. In 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 1458-1464, 2013.
[21] 陳宣好. 具快速變換與跳躍能力之輪腳機組開發. 工學院機械工程學系, 國立台灣大學, 2020.
[22] Xuanqi Zeng, Songyuan Zhang, Hongji Zhang, Xu Li, Haitao Zhou, and Yili Fu. Leg trajectory planning for quadruped robots with high-speed trot gait. Applied Sciences, 9(7):1508, 2019.
[23] Matt Haberland, JG Daniël Karssen, Sangbae Kim, and Martijn Wisse. The effect of swing leg retraction on running energy efficiency. In 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 3957-3962, IEEE, 2011.
[24] Kyeong Yong Kim and Jong Hyeon Park. Ellipse-based leg-trajectory generation for galloping quadruped robots. Journal of mechanical science and technology, 22:2099-2106, 2008.
[25] N Hogan. Impedance control: an approach to manipulation: I-theory. ii-implementation. iii-application. ASME, Transations, Journal of Dynamic Systems, Measurement and Control (ISSN 0022-0434), 107, 1985.
[26] MM Rahman, R Ikeura, and K Mizutani. Investigating the impedance characteristic of human arm for development of robots to co-operate with human operators. In IEEE SMC’99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No. 99CH37028), volume 2, pages 676-681, IEEE, 1999.
[27] Zhijun Li, Shuzhi Sam Ge, and Sibang Liu. Contact-force distribution optimization and control for quadruped robots using both gradient and adaptive neural networks. IEEE Transactions on Neural Networks and Learning Systems, 25(8):1460-1473, 2014.
[28] C. Dario Bellicoso, Fabian Jenelten, Péter Fankhauser, Christian Gehring, Jemin Hwangbo, and Marco Hutter. Dynamic locomotion and whole-body control for quadrupedal robots. In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 3359-3365, 2017.
[29] 陳宥儒. 以中樞模式發生器結合踝關節力覺化進行四足機器人之步態生成控制與變換. 工學院機械工程學系, 國立臺灣大學, 2022.
[30] 莊源誠. 結合雙自由度輸足模組之四足機器人及其足部混合控制與全身力補償控制之開發. 工學院機械工程學系, 國立臺灣大學, 2023.
[31] Fares J Abu-Dakka and Matteo Saveriano. Variable impedance control and learning—a review. Frontiers in Robotics and AI, 7:590681, 2020.
[32] 王華璋. 輪腳複合機器人之穩定輪腳轉換策略. 工學院機械工程學系, 國立臺灣大學, 2023.
[33] K-k Lee and M Buss. Force tracking impedance control with variable target stiffness. IFAC Proceedings Volumes, 41(2):6751-6756, 2008.
[34] Chao Li, Zhi Zhang, Guihua Xia, Xinru Xie, and Qidan Zhu. Efficient force control learning system for industrial robots based on variable impedance control. Sensors, 18(8):2539, 2018.
[35] Steven G. Johnson. The NLopt nonlinear-optimization package. https://github.com/stevengj/nlopt, 2007.
[36] Sangli Teng, Dianhao Chen, William Clark, and Maani Ghaffari. An error-state model predictive control on connected matrix lie groups for legged robot control. In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 8850-8857, IEEE, 2022.
[37] Kevin M Lynch and Frank C Park. Modern robotics. Cambridge University Press, 2017.
[38] Webots. http://www.cyberbotics.com. Open-source Mobile Robot Simulation Software.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/94861-
dc.description.abstract實驗室第三代輪足複合機器人,結合「輪」於平坦地形高效移動的特性,以及「足」式機器人能於崎嶇地形移動的特性,使機器人在兼顧運動能量效率的同時,於各類崎嶇地形運動。
本研究基於實驗室第三代輪足複合機器人,期望達成輪足機器人能以足模式能夠穩定平穩行走的最終成果。於此研究中,針對第三代輪足機構,提出輪足機構的簡化動力學模型,使得能以更簡單、快速的方式求解輪足模組於空中運動時,對於機身所造成的慣性力影響及運動所需的馬達扭矩。
結合生物軀幹對於接觸力控制的概念,針對輪足模組提出力追蹤控制器架構,以導納控制為基礎,透過自適應彈簧阻尼系統之剛性,使輪足模組於行走過程之中,能夠足尖點的地面接觸力進行控制。
本研究針對輪足機器人之行走步態提出新一代全機控制架構,整合來自機身狀態估測器的資訊,分別對於滯空腳及觸地腳提出新的控制方法,以貝茲曲線規劃滯空腳軌跡;以全機力分布控制器分配觸地腳之地面接觸力,以全機狀態補償器補償機身當前位置、姿態,並以輪足力追蹤控制器進行控制。
最終,本研究以模擬及實體實驗驗證全機狀態控制器的控制成效,新一代全機控制架構可以有效減少機器人行走時地面之衝擊力,使得行走步態之穩定性有顯著改善。
zh_TW
dc.description.abstractThe third-generation wheel-legged robot developed by our laboratory combines the efficient movement characteristics of ”wheels” on flat terrain with the ability of ”legged” robots to navigate rough terrain. This combination allows the robot to maintain energy efficiency while moving across various terrains.
This research aims to achieve the ultimate goal of enabling the wheel-legged robot to walk stably and smoothly in leg mode, based on the third-generation wheel-legged robot. In this study, a simplified dynamic model of the wheel-legged mechanism is proposed, allowing for a more straightforward and faster solution to the inertial forces affecting the robot body and the motor torques required for movement during swing phase motion.
Incorporating the concept of contact force control from biological structures, a force-tracking controller framework for the wheel-legged module is proposed. Based on admittance control, the rigidity of the adaptive spring-damping system is used to control the ground contact force at the toe points during the walking process.
This research proposes a new generation of Whole-Body Control architecture for the walking gait of the wheel-legged robot. It integrates information from the body state estimator and proposes new control methods for both the swing and stance legs. The swing leg trajectory is planned using Bezier curves, while the ground contact forces of the stance legs are distributed using a whole-body force distribution controller. The body position and posture are compensated using a whole-body position compensator, and control is executed through the wheel-legged force-tracking controller.
Finally, the effectiveness of the Whole-Body Control architecture is verified through simulations and physical experiments. The new generation of Whole-Body Control architecture can significantly reduce the impact of ground reaction forces generated by the swing leg during walking, leading to a noticeable improvement in gait stability.
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dc.description.tableofcontents口試委員審定書i
誌謝iii
摘要v
Abstract vii
目次ix
圖次xiii
表次xv
第一章緒論1
1.1 前言. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 文獻回顧. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2.1 四足機器人回顧. . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2.2 輪足複合式機器人回顧. . . . . . . . . . . . . . . . . . . . . . . 2
1.2.3 四足機器人滯空腳軌跡規劃回顧. . . . . . . . . . . . . . . . . . 5
1.2.4 四足機器人觸地腳控制方法回顧. . . . . . . . . . . . . . . . . . 6
1.3 研究動機. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.4 貢獻. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.5 論文架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
第二章實驗平台架構11
2.1 前言. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.2 實驗平台. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.2.1 第三代輪腳複合機構. . . . . . . . . . . . . . . . . . . . . . . . 11
2.2.2 單足模組. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.2.3 輪足複合式機器人. . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.2.3.1 機身機構. . . . . . . . . . . . . . . . . . . . . . . . 14
2.2.3.2 機電架構. . . . . . . . . . . . . . . . . . . . . . . . 18
2.2.3.3 軟韌體架構. . . . . . . . . . . . . . . . . . . . . . . 19
第三章輪足機構簡化動力學模型23
3.1 前言. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2 運動學模型. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2.1 順向運動學模型. . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2.2 虛功法. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.3 輪足模組動力學模型. . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.3.1 輪足模組簡化動力學模型推導. . . . . . . . . . . . . . . . . . . 29
3.3.2 動力學模型實驗驗證. . . . . . . . . . . . . . . . . . . . . . . . 32
第四章輪足模組力追蹤控制器35
4.1 前言. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
4.2 輪足模組力追蹤控制器. . . . . . . . . . . . . . . . . . . . . . . . . 36
4.2.1 輪足模組阻抗控制器. . . . . . . . . . . . . . . . . . . . . . . . 36
4.2.2 輪足模組力追蹤控制器. . . . . . . . . . . . . . . . . . . . . . . 40
4.2.3 輪足模組力追蹤實驗. . . . . . . . . . . . . . . . . . . . . . . . 42
4.2.3.1 不同觸地點之力追蹤實驗. . . . . . . . . . . . . . . 43
4.2.3.2 不同方向水平分力之力追蹤實驗. . . . . . . . . . . 44
4.2.3.3 不同地面材質之力追蹤實驗. . . . . . . . . . . . . . 44
第五章輪足機器人全機狀態控制器51
5.1 前言. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
5.2 控制架構. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
5.3 機身質心運動軌跡規劃. . . . . . . . . . . . . . . . . . . . . . . . . 53
5.4 滯空腳運動軌跡規劃. . . . . . . . . . . . . . . . . . . . . . . . . . 56
5.5 全機力分布控制器. . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5.5.1 機身剛體動力學. . . . . . . . . . . . . . . . . . . . . . . . . . . 58
5.5.2 追蹤誤差動態. . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
5.5.3 最佳化問題定義. . . . . . . . . . . . . . . . . . . . . . . . . . . 63
5.6 機身狀態補償器. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5.7 輪足機器人行走實驗. . . . . . . . . . . . . . . . . . . . . . . . . . 67
5.7.1 模擬實驗. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
5.7.2 實體實驗. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
第六章結論與未來展望81
6.1 結論. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
6.2 未來展望. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
參考文獻85
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dc.language.isozh_TW-
dc.subject全機力控制zh_TW
dc.subject四足機器人zh_TW
dc.subject輪足複合模組zh_TW
dc.subject力追蹤控制zh_TW
dc.subjectQuadrupeden
dc.subjectWheel-leg moduleen
dc.subjectForce tracking controlen
dc.subjectWhole-body controlen
dc.title基於足部力追蹤控制之輪足複合式四足機器人 全機控制架構開發zh_TW
dc.titleDevelopment of a Whole-body Control Architecture for a Wheel-legged Hybrid Quadruped Robot Based on Foot Force Tracking Controlen
dc.typeThesis-
dc.date.schoolyear112-2-
dc.description.degree碩士-
dc.contributor.oralexamcommittee連豊力;顏炳郎zh_TW
dc.contributor.oralexamcommitteeFeng-Li Lian;Ping-Lang Yenen
dc.subject.keyword四足機器人,輪足複合模組,力追蹤控制,全機力控制,zh_TW
dc.subject.keywordQuadruped,Wheel-leg module,Force tracking control,Whole-body control,en
dc.relation.page89-
dc.identifier.doi10.6342/NTU202403316-
dc.rights.note同意授權(全球公開)-
dc.date.accepted2024-08-10-
dc.contributor.author-college工學院-
dc.contributor.author-dept機械工程學系-
dc.date.embargo-lift2029-08-05-
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