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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 羅仁權(Ren C. Luo) | |
dc.contributor.author | Chien-An Chen | en |
dc.contributor.author | 陳建安 | zh_TW |
dc.date.accessioned | 2021-06-15T11:47:18Z | - |
dc.date.available | 2016-09-13 | |
dc.date.copyright | 2016-09-13 | |
dc.date.issued | 2016 | |
dc.date.submitted | 2016-08-12 | |
dc.identifier.citation | [1] S. Kajita, F. Kanehiro, K. Kaneko, K. Yokoi, and H. Hirukawa, “The 3D linear inverted pendulum mode: A simple modeling for a biped walking pattern generation,” in Proc. IEEE Int. Conf. Intell. Robots Syst., 2001, pp. 239–246.
[2] R. C. Luo, P. H. Chang, J. Sheng, S. C. Gu, and C. H. Chen, “Arbitrary Biped Robot Foot Gaiting Based on Non-Constant COM Height,” 2013 IEEE-RAS International Conference on Humanoid Robots. [3] R. C. Luo, J. Sheng, P. H. Chang, C. C. Chen, and C. I. Lin, “Biped Robot Push and Recovery Using Flywheel Model Based Walking Perturbation Counteraction,” 2013 IEEE-RAS International Conference on Humanoid Robots. [4] N. Kalamian and M. Farrokhi, “Dynamic Walking of Biped Robots with Obstacles Using Predictive Controller”, in Computer and Knowledge Engineering (ICCKE), 2011 1st International Conference on, 2011, pp.105-110. [5] Atlas - The Agile Anthropomorphic Robot [online]. Available: http://www.bostondynamics.com/robot_Atlas.html [6] M. Vukobratović, D. Juričić, “Zero-Moment Point- Thirty Five Years of Its Life”, IEEE International Journal of Humanoid Robotics, pp.157~173, 2004. [7] A. Takanishi, M. Ishida, Y. Yamazaki, and I. Kato, “The realization of dynamic walking robot WL-10RD,” in Proc. Int. Conf. Advanced Robotics., 1985, pp. 459-466. [8] C. L. Shih, Y. Z. Li, S. Churng, T. T. Lee, and W. A. Cruver, “Trajectory synthesis and physical admissibility for a biped robot during the single support phase,” in Proc. IEEE Int. Conf. Robot. Autom., 1990, pp. 1646–1652. [9] S. Kajita, F. Kanehiro, K. Kaneko, K. Yokoi, and H. Hirukawa, “The 3D linear inverted pendulum mode: A simple modeling for a biped walking pattern generation,” in Proc. IEEE Int. Conf. Intell. Robots Syst., 2001, pp. 239–246. [10] S. Kajita, O. Matsumoto, and M. Saigo, “Real-time 3D Walking Pattern Generation for a Biped Robot with Telescopic Legs,” Proc. of IEEE Int. Conf. on Robotics and Automation, pp. 2299-2036, 2001. [11] S. Kajita, F. Kanehiro, K. Kaneko, K. Fujiwara, K. Yokoi, and H. Hirukawa, “A Realtime Pattern Generator for Biped Walking,” Proc. of the 2002 ICRA, pp.31-27, 2002. [12] K. Erbatur and O. Kurt, “Humanoid walking robot control with natural ZMP references,” in Proc. 32nd Annu. Conf. IEEE Ind. Electron. Soc., 2006, pp. 4100–4106. [13] K. Erbatur and O. Kurt, “Natural ZMP trajectories for biped robot reference generation,” IEEE Trans. Ind. Electron., vol. 56, no. 3, pp. 835–845, Mar. 2009. [14] J. H. Park and K. D. Kim, “Biped robot walking using gravity compensated inverted pendulum mode and computed torque control,” in Proc. IEEE Int. Conf. Robot. Autom., 1998, pp. 3528–3533. [15] J. H. Park and H. C. Cho, “An on-line trajectory modifier for the base link of biped robots to enhance locomotion stability,” in Proc. IEEE Int. Conf. Robot. Autom., 2000, pp. 3353–3358. [16] T. Sato, S. Sakaino, and K. Ohnishi, “Real-time walking trajectory generation method with three-mass models at constant body height for three-dimensional biped robots,” Industrial Electronics, IEEE Transactions on 58.2 (2011): 376-383. [17] S. Kajita , M. Morisawa , K. Harada , K. Kaneko , F. Kanehiro , K. Fujiwara and H. Hirukawa, “Biped walking pattern generation by using preview control of zero-moment point,” Proc. IEEE Int. Conf. Robot. Autom. (ICRA 2003), vol. 2, pp.1620 -1626. [18] J. Park and Y. Youm, “General zmp preview control for bipedal walking,” in Proceedings of the 2007 IEEE International Conference on Robotics and Automation, Roma, Italy, 2007, pp. 2682-2687. [19] J. Pratt, J. Carff, S. Drakunov, and A. Goswami, “Capture point: A step toward humanoid push recovery,” in IEEE/RAS Int. Conf. on Humanoid Robots, 2006, pp. 200–207. [20] A. L. Hof, “The ’extrapolated center of mass’ concept suggests a simple control of balance in walking,” Human Movement Science, vol. 27, no. 1, 2008. [21] Biped humanoid robot group WABIAN-2R (2006-) [online]. Available: http://www.takanishi.mech.waseda.ac.jp/top/research/wabian/ [22] Englsberger, Johannes, et al. 'Bipedal walking control based on capture point dynamics.' 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2011. [23] Englsberger, Johannes, and Christian Ott. 'Integration of vertical com motion and angular momentum in an extended capture point tracking controller for bipedal walking.' 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012). IEEE, 2012. [24] Gracovetski, S. (1988) The Spinal Engine. Springer, Berlin. [25] J. Yamaguchi, A. Takanishi, and I. Kato, Development of a biped walking robot compensating for three-axis moment by trunk motion, in Proc. IEEE/RSJ Int. Conf. Intelligent Robotics and Systems, 1993, pp. 561-566. [26] Y. Ogura, H. Aikawa, H. Lim, and A. Takanishi, Development of a human-like walking robot having two 7-DOF legs and a 2-DOF waist, Proc. IEEE Int. Conference on Robotics and Automation, pp. 134-139, 2004. [27] Zhang, Wen, et al. ”Human-like walking patterns with pelvic rotation for a humanoid robot.” Intelligent Control and Automation (WCICA), 2014 11th World Congress on. IEEE, 2014. [28] Liu, Jing, Uwe Schwiegelshohn, and Oliver Urbann. ”Stable walking of a bipedal humanoid robot involving three-dimensional upper body motion.” Humanoid Robots (Humanoids), 2014 14th IEEE-RAS International Conference on. IEEE, 2014. [29] P.B.Wieber, “Trajectory free linear model predictive control for stable walking in the presence of strong perturbation,” IEEE - International Conference on Humanoids, 2006, pp. 137-142. [30] Sobajima, Masafumi, et al. “Bipedal walking control of humanoid robots by arm-swing.” SICE Annual Conference (SICE), 2013 Proceedings of. IEEE, 2013, pp. 313-318. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/49771 | - |
dc.description.abstract | 雙足機器人相較於輪型機器人,在適應人類居住環境或克服天然不平地形有很大的優勢,而擁有兩隻腳的人型機器人則更能滿足為人類服務的需求。但在為人類服務之前,機器人必須有能力維持自身的穩定來行走在各種環境中,例如不平的地面,上下樓梯,或滿是障礙的空間等。至今已有非常多的理論被提出並使得機器人可以穩定的行走,預看控制就是其中非常重要的一項里程碑。基於先前研究人員提出的簡化機器人模型,例如單質心模型或三質心模型,在事先規劃好的腳步之下,我們可以利用預看控制來達到能讓機器人穩定行走的各軸角度軌跡規劃。
在本論文中,我們提出兩個可以增進機器人行走能力的全身性行走軌跡規劃演算法,其一是腰部最佳軌跡規劃演算法以及上半身動作補償,透過腰部數學模型的建立以及簡化,我們可以利用線性規劃解算器來求得最佳化的腰部軌跡,其效果能使得機器人夠擁有更快的走路速度以及更好運動能力,跨出原本無法達到的更大步伐。其二是線上走路軌跡規劃演算法,相較於先前必須先做好腳步規劃的離線版本,我們可以選擇使用人為控制或是機器人自動辨識的方式,來即時改變機器人的行走方向,結合近年的機器人行走理論,規劃出適當行走軌跡。最後,我們透過圖表來比較加上腰部運動軌跡之後的走路實驗,其行走表現以及運動能力均得到了提升,而我們所設計的即時行走軌跡規劃也確實能提供穩定且較為快速的走路運動。 | zh_TW |
dc.description.abstract | Comparing with wheeled robots, biped robots have more flexibility of adapting to living environment of humans and confronting with uneven terrain. And biped robots with upper body and two arms, or humanoid robots, are more capable of meeting humans’ demand, for example, cleaning rooms or serve drinks. However, before starting to serve humans, the humanoid robot itself need to guarantee its stability while walking in all kinds of environment, such as uneven terrain, stairs and spaces occupied by obstacles. So far, there have been many successfully developed theories and implementation of walking pattern generator that can perform stable walking for humanoid robot, and preview control theory is one of the most important one in the field. Based on simplified model for humanoid robots with complex structures, linear inverted pendulum model for example, we can do the footstep planning in advance and utilize the preview control theory to generate walking patterns with whole-body motions.
In this thesis, we propose two trajectory generation algorithms that can greatly enhance the capability of a walking robot. One of the algorithms is the waist trajectory generation algorithm that can generate optimal waist motions and upper body compensation motions. By formulating and simplifying the waist trajectory generation problem, we are able to utilize the state-of-the-art linear programming solver to generate optimal waist motions. The generated optimal waist motions then increase the walking speed and exercising capability of humanoid robots, lengthen the walking stride for example. The second algorithm we proposed in this thesis is the online walking pattern generator. The difference of the proposed online walking pattern generator and the previous offline walking pattern generator in our lab is that the robot’s walking direction can now be changed by humans or the robot itself in any time. The algorithm exploits the concept of capture points and plans proper footsteps and walking patterns. Finally, the experiments show that two proposed trajectory generation algorithms do increase walking speed, lengthen walking strides and still preserve stability. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T11:47:18Z (GMT). No. of bitstreams: 1 ntu-105-R02943146-1.pdf: 3373523 bytes, checksum: ff5650015869cfeba48eef2a74748230 (MD5) Previous issue date: 2016 | en |
dc.description.tableofcontents | 誌謝 i
中文摘要 ii ABSTRACT iii TABLE OF CONTENTS v LIST OF FIGURES vii LIST OF TABLES ix Chapter 1 Introduction 1 1.1 Motivation and Objective 1 1.2 State-of-the-art Humanoid Robots 2 1.2.1 DRC-Hubo+ 2 1.2.2 ATLAS 4 1.3 Literature Review 6 1.3.1 3D Linear Inverted Pendulums Model and Zero-moment Point 6 1.3.2 Capture Point Dynamics 8 1.4 Organization 11 Chapter 2 System Overview 13 2.1 Hardware 13 2.2 Software 19 2.2.1 EtherCAT 19 2.2.2 System Architecture 20 2.3 Robot Coordinate System 22 Chapter 3 Optimal Waist Trajectory Generation 28 3.1 Problem Formulation 28 3.2 Problem Simplification 30 3.2.1 Linearization 30 3.2.2 Receding Horizon Control 34 3.3 Swinging Arm Trajectory Generation 35 3.4 Proposed Control Scheme 36 Chapter 4 Online Walking Pattern Generation 39 4.1 Problem Declaration 40 4.2 Walking Pattern Generation Algorithm 42 4.2.1 Preprocess for Planning a Step 42 4.2.2 Whole Online Walking Pattern Generator 47 Chapter 5 Simulation and Experiment 51 5.1 Optimal Waist Trajectory Analysis 51 5.2 Online Walking Pattern Analysis 59 5.2.1 Experimental Result with Basic Setup 59 5.2.2 Comparison between Different Walking Parameter 65 Chapter 6 Conclusions and Future Works 70 6.1 Conclusions 70 6.2 Future works 71 REFERENCE 72 | |
dc.language.iso | en | |
dc.title | 人形機器人即時行走軌跡規劃及最佳腰部軌跡生成 | zh_TW |
dc.title | Humanoid Robot Online Walking Pattern Generation with Optimal Waist Trajectories | en |
dc.type | Thesis | |
dc.date.schoolyear | 104-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 陽毅平(Yee-Pien Yang),康仕仲(Shih-Chung Kang) | |
dc.subject.keyword | 人型機器人,即時行走軌跡規劃,腰部軌跡設計, | zh_TW |
dc.subject.keyword | Humanoid Robot,Online Walking Pattern Generator,Waist Trajectory Generation, | en |
dc.relation.page | 76 | |
dc.identifier.doi | 10.6342/NTU201602422 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2016-08-13 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
顯示於系所單位: | 電機工程學系 |
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