請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/52873
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 | Ting-Wei Jen | en |
dc.contributor.author | 任庭緯 | zh_TW |
dc.date.accessioned | 2021-06-15T16:31:43Z | - |
dc.date.available | 2020-08-28 | |
dc.date.copyright | 2015-08-28 | |
dc.date.issued | 2015 | |
dc.date.submitted | 2015-08-13 | |
dc.identifier.citation | References
[1] T. Aoyama, Y. Hasegawa, K. Sekiyama, and T. Fukuda, 'Stabilizing and direction control of efficient 3-D biped walking based on PDAC,' IEEE/ASME Transactions on Mechatronics, Vol. 14, No. 6, pp. 712-718, 2009. [2] T. Bailey and H. Durrant-Whyte, 'Simultaneous localization and mapping (SLAM): Part II,' IEEE Robotics & Automation Magazine, Vol. 13, No. 3, pp. 108-117, 2006. [3] L. Baudouin, N. Perrin, T. Moulard, F. Lamiraux, O. Stasse, and E. Yoshida, 'Real-time replanning using 3d environment for humanoid robot,' Proc. of IEEE International Conference on Humanoid Robots, Bled, Slovenia, pp. 584-589, 2011. [4] S. Candido, K. Yong-Tae, and S. Hutchinson, 'An improved hierarchical motion planner for humanoid robots,' Proc. of the 8th IEEE International Conference on Humanoid Robots, Daejeon, Korea, pp. 654-661, 2008. [5] J. Chestnutt, J. Kuffner, K. Nishiwaki, and S. Kagami, 'Planning biped navigation strategies in complex environments,' Proc. of IEEE International Conference on Humanoid Robots, Munich, Germany, 2003. [6] J. Chestnutt, M. Lau, G. Cheung, J. Kuffner, J. Hodgins, and T. Kanade, 'Footstep Planning for the Honda ASIMO Humanoid,' Proc. of IEEE International Conference on Robotics and Automation, pp. 629-634, 2005. [7] J. Chestnutt, K. Nishiwaki, J. Kuffner, and S. Kagami, 'An adaptive action model for legged navigation planning,' Proc. of IEEE International Conference on Humanoid Robots, pp. 196-202, 2007. [8] Y. Choi, D. Kim, and B.-J. You, 'On the walking control for humanoid robot based on the kinematic resolution of com jacobian with embedded motion,' Proc. of IEEE International Conference on Robotics and Automation, Orlando, USA, pp. 2655-2660, 2006. [9] H. Choset and K. Nagatani, 'Topological simultaneous localization and mapping (SLAM): toward exact localization without explicit localization,' IEEE International Conference on Robotics and Automation, Vol. 17, No. 2, pp. 125-137, 2001. [10] R. Cupec, G. Schmidt, and O. Lorch, 'Experiments in Vision-Guided Robot Walking in a Structured Scenario,' Proc. of IEEE International Symposium on Industrial Electronics, Dubrovnik, Hrvatska, Vol. 4, pp. 1581-1586, 2005. [11] R. Deits and R. Tedrake, 'Footstep planning on uneven terrain with mixed-integer convex optimization,' Proc. of IEEE International Conference on Humanoid Robots, Madrid, Spain, pp. 279-286, 2014. [12] F. Dellaert, D. Fox, W. Burgard, and S. Thrun, 'Monte carlo localization for mobile robots,' Proc. of IEEE International Conference on Robotics and Automation, Detroit, U.S., Vol. 2, pp. 1322-1328, 1999. [13] H. Durrant-Whyte and T. Bailey, 'Simultaneous localization and mapping: part I,' IEEE Robotics & Automation Magazine, Vol. 13, No. 2, pp. 99-110, 2006. [14] G. Endo, J. Morimoto, T. Matsubara, J. Nakanishi, and G. Cheng, 'Learning CPG-based biped locomotion with a policy gradient method: Application to a humanoid robot,' The International Journal of Robotics Research, Vol. 27, No. 2, pp. 213-228, 2008. [15] F. Endres, J. Hess, N. Engelhard, J. Sturm, D. Cremers, and W. Burgard, 'An evaluation of the RGB-D SLAM system,' Proc. of IEEE International Conference on Robotics and Automation, Saint Paul, U.S., pp. 1691-1696, 2012. [16] E. T. Esfahani and M. H. Elahinia, 'Stable walking pattern for an SMA-actuated biped,' IEEE/ASME Transactions on Mechatronics, Vol. 12, No. 5, pp. 534-541, 2007. [17] D. Fox, W. Burgard, F. Dellaert, and S. Thrun, 'Monte carlo localization: Efficient position estimation for mobile robots,' AAAI/IAAI, Vol. 1999, pp. 343-349, 1999. [18] J. Garimort and A. Hornung, 'Humanoid navigation with dynamic footstep plans,' Proc. of IEEE International Conference on Robotics and Automation, Shanghai, China, pp. 3982-3987, 2011. [19] T. Geng and J. Q. Gan, 'Planar biped walking with an equilibrium point controller and state machines,' IEEE/ASME Transactions on Mechatronics, Vol. 15, No. 2, pp. 253-260, 2010. [20] J.-S. Gutmann, M. Fukuchi, and M. Fujita, '3D perception and environment map generation for humanoid robot navigation,' The International Journal of Robotics Research, Vol. 27, No. 10, pp. 1117-1134, 2008. [21] J.-S. Gutmann, M. Fukuchi, and M. Fujita, 'Real-time path planning for humanoid robot navigation,' Proc. of International Joint Conference on Artificial Intelligence, Vol. 19, p. 1232, 2005. [22] J. S. Gutmann, M. Fukuchi, and M. Fujita, 'A modular architecture for humanoid robot navigation,' Proc. of IEEE International Conference on Humanoid Robots, Tsukuba, Japan, pp. 26-31, 2005. [23] K. Harada, S. Kajita, K. Kaneko, and H. Hirukawa, 'An analytical method for real-time gait planning for humanoid robots,' International Journal of Humanoid Robotics, Vol. 3, No. 01, pp. 1-19, 2006. [24] K. Hauser, T. Bretl, J.-C. Latombe, K. Harada, and B. Wilcox, 'Motion planning for legged robots on varied terrain,' The International Journal of Robotics Research, Vol. 27, No. 11-12, pp. 1325-1349, 2008. [25] K. Hauser, T. Bretl, and J. C. Latombe, 'Non-gaited humanoid locomotion planning,' Proc. of IEEE International Conference on Humanoid Robots, Tsukuba, Japan, pp. 7-12, 2005. [26] P. Henry, M. Krainin, E. Herbst, X. Ren, and D. Fox, 'RGB-D mapping: Using depth cameras for dense 3D modeling of indoor environments,' Proc. of International Symposium on Experimental Robotics, 2010. [27] S. Hong, Y. Oh, D. Kim, and B.-J. You, 'Real-time walking pattern generation method for humanoid robots by combining feedback and feedforward controller,' IEEE Transactions on Industrial Electronics, Vol. 61, No. 1, pp. 355-364, 2014. [28] A. Hornung and M. Bennewitz, 'Adaptive level-of-detail planning for efficient humanoid navigation,' Proc. of IEEE International Conference on Robotics and Automation, Saint Paul, U.S., pp. 997-1002, 2012. [29] A. Hornung, A. Dornbush, M. Likhachev, and M. Bennewitz, 'Anytime search-based footstep planning with suboptimality bounds,' Proc. of IEEE International Conference on Humanoid Robots, Osaka, Japan, pp. 674-679, 2012. [30] A. Hornung, D. Maier, and M. Bennewitz, 'Search-based footstep planning,' Proc. of ICRA-Workshop on Progress and Open Problems in Motion Planning and Navigation for Humanoids, Karlsruhe, Germany, 2013. [31] A. Hornung, K. M. Wurm, and M. Bennewitz, 'Humanoid robot localization in complex indoor environments,' Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, pp. 1690-1695, 2010. [32] H.-P. Huang, J.-L. Yan, and T.-H. Cheng, 'State-incremental optimal control of 3D COG pattern generation for humanoid robots,' Advanced Robotics, Vol. 27, No. 3, pp. 175-188, 2013. [33] S. Kajita, F. Kanehiro, K. Kaneko, K. Fujiwara, K. Harada, K. Yokoi, and H. Hirukawa, 'Biped walking pattern generation by using preview control of zero-moment point,' Proc. of IEEE International Conference on Robotics and Automation, Vol. 2, pp. 1620-1626, 2003. [34] S. Kajita, F. Kanehiro, K. Kaneko, K. Fujiwara, K. Yokoi, and H. Hirukawa, 'A realtime pattern generator for biped walking,' Proc. of IEEE International Conference on Robotics and Automation, Vol. 1, pp. 31-37, 2002. [35] 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,' Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, Maui, U.S., Vol. 1, pp. 239-246, 2001. [36] S. Kajita, M. Morisawa, K. Harada, K. Kaneko, F. Kanehiro, K. Fujiwara, and H. Hirukawa, 'Biped walking pattern generator allowing auxiliary zmp control,' Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China, pp. 2993-2999, 2006. [37] S. Karaman, M. R. Walter, A. Perez, E. Frazzoli, and S. Teller, 'Anytime Motion Planning using the RRT*,' Proc. of IEEE International Conference on Robotics and Automation, Shanghai, China, pp. 1478-1483, 2011. [38] S. Koenig and M. Likhachev, 'D* Lite,' Proc. of National Conference on Artificial Intelligence, pp. 476-483, 2002. [39] S. Koenig and M. Likhachev, 'Fast replanning for navigation in unknown terrain,' IEEE Transactions on Industrial Electronics, Vol. 21, No. 3, pp. 354-363, 2005. [40] J. Kuffner, S. Kagami, K. Nishiwaki, M. Inaba, and H. Inoue, 'Online footstep planning for humanoid robots,' Proc. of IEEE International Conference on Robotics and Automation, Vol. 1, pp. 932-937, 2003. [41] J. Kuffner, K. Nishiwaki, S. Kagami, M. Inaba, and H. Inoue, 'Motion planning for humanoid robots,' Proc. of International Symposium Robotics Research, pp. 365-374, 2005. [42] J. J. Kuffner and S. M. LaValle, 'RRT-connect: An efficient approach to single-query path planning,' Proc. of IEEE International Conference on Robotics and Automation, San Francisco, U.S., Vol. 2, pp. 995-1001, 2000. [43] J. J. Kuffner Jr, K. Nishiwaki, S. Kagami, M. Inaba, and H. Inoue, 'Footstep planning among obstacles for biped robots,' Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, Maui, U.S., Vol. 1, pp. 500-505, 2001. [44] O. Kurt and K. Erbatur, 'Biped robot reference generation with natural ZMP trajectories,' Proc. of IEEE International Workshop on Advanced Motion Control, Istanbul, Turkey, pp. 403-410, 2006. [45] S. M. LaValle and J. J. Kuffner, 'Randomized kinodynamic planning,' The International Journal of Robotics Research, Vol. 20, No. 5, pp. 378-400, 2001. [46] S. M. Lavalle and J. J. Kuffner Jr, 'Rapidly-Exploring Random Trees: Progress and Prospects,' Proc. of Algorithmic and Computational Robotics: New Directions, 2000. [47] M. Likhachev, D. I. Ferguson, G. J. Gordon, A. Stentz, and S. Thrun, 'Anytime Dynamic A*: An Anytime, Replanning Algorithm,' Proc. of The International Conference on Automated Planning & Scheduling, Monterey, U.S., pp. 262-271, 2005. [48] M. Likhachev, G. J. Gordon, and S. Thrun, 'ARA*: Anytime A* with provable bounds on sub-optimality,' Proc. of Advances in Neural Information Processing Systems, p. None, 2003. [49] M. Likhachev and A. Stentz, 'R* search,' Lab Papers (GRASP), p. 23, 2008. [50] D. Maier, A. Hornung, and M. Bennewitz, 'Real-time navigation in 3D environments based on depth camera data,' Proc. of IEEE-RAS International Conference on Humanoid Robots, Osaka, Japan, pp. 692-697, 2012. [51] D. Maier, C. Lutz, and M. Bennewitz, 'Integrated perception, mapping, and footstep planning for humanoid navigation among 3d obstacles,' Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan, pp. 2658-2664, 2013. [52] P. Michel, J. Chestnutt, S. Kagami, K. Nishiwaki, J. Kuffner, and T. Kanade, 'GPU-accelerated real-time 3D tracking for humanoid locomotion and stair climbing,' Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, U.S., pp. 463-469, 2007. [53] P. Michel, J. Chestnutt, S. Kagami, K. Nishiwaki, J. Kuffner, and T. Kanade, 'Online environment reconstruction for biped navigation,' Proc. of IEEE International Conference on Robotics and Automation, Orlando, U.S., pp. 3089-3094, 2006. [54] P. Michel, J. Chestnutt, J. Kuffner, and T. Kanade, 'Vision-guided humanoid footstep planning for dynamic environments,' Proc. of IEEE-RAS International Conference on Humanoid Robots, Tsukuba, Japan, pp. 13-18, 2005. [55] M. Montemerlo and S. Thrun, 'FastSLAM 2.0,' FastSLAM: A Scalable Method for the Simultaneous Localization and Mapping Problem in Robotics, pp. 63-90, 2007. [56] K. Nishiwaki, J. Chestnutt, and S. Kagami, 'Autonomous navigation of a humanoid robot over unknown rough terrain using a laser range sensor,' The International Journal of Robotics Research, Vol. 31, No. 11, pp. 1251-1262, 2012. [57] K. Okada, T. Ogura, A. Haneda, and M. Inaba, 'Autonomous 3D walking system for a humanoid robot based on visual step recognition and 3D foot step planner,' Proc. of IEEE International Conference on Robotics and Automation, pp. 623-628, 2005. [58] N. Perrin, O. Stasse, L. Baudouin, F. Lamiraux, and E. Yoshida, 'Fast Humanoid Robot Collision-Free Footstep Planning Using Swept Volume Approximations,' IEEE Transactions on Robotics, Vol. 28, No. 2, pp. 427-439, 2012. [59] N. Perrin, O. Stasse, F. Lamiraux, Y. J. Kim, and D. Manocha, 'Real-time footstep planning for humanoid robots among 3D obstacles using a hybrid bounding box,' Proc. of IEEE International Conference on Robotics and Automation, Saint Paul, U.S., pp. 977-982, 2012. [60] V. Sangwan and S. K. Agrawal, 'Differentially flat design of bipeds ensuring limit cycles,' IEEE/ASME Transactions on Mechatronics, Vol. 14, No. 6, pp. 647-657, 2009. [61] S. Thrun, D. Fox, W. Burgard, and F. Dellaert, 'Robust Monte Carlo localization for mobile robots,' Artificial Intelligence, Vol. 128, No. 1, pp. 99-141, 2001. [62] L. Tsai-Yen, C. Pei-Feng, and H. Pei-Zhi, 'Motion planning for humanoid walking in a layered environment,' Proc. of IEEE International Conference on Robotics and Automation, Vol. 3, pp. 3421-3427 vol.3, 2003. [63] N. Van der Noot and A. Barrea, 'Zero-Moment Point on a bipedal robot under bio-inspired walking control,' Proc. of IEEE Mediterranean Electrotechnical Conference, Beirut, Lebanon, pp. 85-90, 2014. [64] P. Vernaza, M. Likhachev, S. Bhattacharya, S. Chitta, A. Kushleyev, and D. D. Lee, 'Search-based planning for a legged robot over rough terrain,' Proc. of IEEE International Conference on Robotics and Automation, Kobe, Japan, pp. 2380-2387, 2009. [65] Z. Xia, J. Xiong, and K. Chen, 'Global navigation for humanoid robots using sampling-based footstep planners,' IEEE/ASME Transactions on Mechatronics, Vol. 16, No. 4, pp. 716-723, 2011. [66] J.-L. Yan and H.-P. Huang, 'A fast and smooth walking pattern generator of biped robot using Jacobian inverse kinematics,' Proc. of Advanced Robotics and Its Social Impacts, 2007. ARSO 2007. IEEE Workshop on, pp. 1-6, 2007. [67] J. L. Yan, Optimized Walking Pattern Generation and Real-time Control for Humanoid Robots, Ph.D. Dissertation, Graduate Insitute of Mechanical Engineering, National Taiwan University, 2012. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/52873 | - |
dc.description.abstract | 本論文提出一套自動導航系統可使機器人感知環境及其變化,並產生相對應的步態軌跡克服當下的環境變化。此方法結合環境感知(Environment Sensing)和步態軌跡規劃器(Footstep Planner),其中環境感知包含了機器人本身所在位置、目標點的位置、以及環境中障礙物的位置及方向。而步態軌跡規劃器則是包含腳步轉換模型(Footstep Transition Model)、成本函數(Cost Function)、還有演算法(Algorithm)。此外,本論文更提出了針對腳步轉換模型的改善方法:動態腳步轉換模型(Dynamic Transition Model)。採用動態腳步轉換模型不僅可以增加規劃軌跡時的完整性(Completeness),更可以增加規劃時的效率(Efficiency)。實驗環境包含靜態(Static)以及動態(Dynamic)來觀測機器人的自動導航系統的表現。本論文理論實現皆透過實驗室自主開發之人形機器人完成。 | zh_TW |
dc.description.abstract | In this thesis, we present a navigation system that combines environment sensing with a footstep planner, allowing humanoid robots to autonomously navigate in unknown and cluttered environments. An environment map including the robot, goal, and obstacle locations is built in real-time from sensors. The footstep planner then computes an optimal sequence of footstep locations through footstep transition model, cost functions, and algorithm. Moreover, dynamic transition model is developed to improve system efficiency and completeness.
The experiment results are used to demonstrate the robot navigating through both static and dynamic environments combined with sensors in real-time. The proposed dynamic transition model shows satisfactory results. All experiments are conducted on the NTU Humanoid robot, Nino, which is constructed by our laboratory. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T16:31:43Z (GMT). No. of bitstreams: 1 ntu-104-R02522832-1.pdf: 7566165 bytes, checksum: 562d771254997817e60caecee9bc97d1 (MD5) Previous issue date: 2015 | en |
dc.description.tableofcontents | 致謝 i
摘要 iii Abstract v Contents vii List of Tables ix List of Figures xi Nomenclature xiii Chapter 1. Introduction 1 1.1 Motivation 1 1.2 Related Works 2 1.3 Contributions 7 1.4 Framework of the Thesis 8 Chapter 2. Locomotion Generation 9 2.1 Introduction 9 2.2 Pattern Generation 9 2.3 Summary 17 Chapter 3. Navigation for Humanoid Robots 19 3.1 Introduction 19 3.2 Footstep Planning 20 3.2.1 Transition Model 20 3.2.2 Cost Function 23 3.2.3 Algorithm 24 3.3 Re-planning 27 3.4 Sensing the Environment 30 3.4.1 Color Segmentation 31 3.4.2 Building the Environment Map 33 3.5 Summary 33 Chapter 4. Dynamic Footstep Planning 35 4.1 Introduction 35 4.2 Dynamic Transition Model 35 4.2.1 Dynamic Transition Model 36 4.2.2 Sub-model Calling Flow 37 4.2.3 Implementations 39 4.3 Summary 45 Chapter 5. Simulations 47 5.1 Simulation Environment 48 5.2 Simulation Scenarios 48 5.2.1 Avoiding obstacle 49 5.2.2 Footstep Re-planning 50 5.3 Summary 52 Chapter 6. Experiments 53 6.1 Specification of the NTU Humanoid Robot 54 6.2 Real-time Navigation/Control System of the NTU Humanoid Robot 55 6.2.1 Real-time Navigation/Control Architecture 55 6.2.2 Sensors 56 6.3 Experimental Results 57 6.3.1 Static Obstacles 58 6.3.2 Dynamic Transition Model 59 6.3.3 Combination of Environment Sensing and Footstep Planner 61 6.3.4 Target Changed 63 6.3.5 Moving Obstacles 65 6.4 Summary 67 Chapter 7. Conclusions and Future Works 69 7.1 Conclusions 69 7.2 Future Works 69 Appendix Dynamic Transition Model 72 References 74 | |
dc.language.iso | en | |
dc.title | 人形機器人之導航與軌跡規劃 | zh_TW |
dc.title | Navigation for Humanoid Robots | en |
dc.type | Thesis | |
dc.date.schoolyear | 103-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 蔡清池,顏炳郎 | |
dc.subject.keyword | 人型機器人,步態軌跡規劃,避障,動態腳步轉換模型,環境感知, | zh_TW |
dc.subject.keyword | Humanoid Robot,footstep planning,obstacle avoidance,dynamic transition model,environment sensing, | en |
dc.relation.page | 79 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2015-08-13 | |
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 | |
---|---|---|---|
ntu-104-1.pdf 目前未授權公開取用 | 7.39 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。