請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/6609
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 | Hsiu-Ting Yang | en |
dc.contributor.author | 楊秀婷 | zh_TW |
dc.date.accessioned | 2021-05-17T09:15:13Z | - |
dc.date.available | 2014-08-01 | |
dc.date.available | 2021-05-17T09:15:13Z | - |
dc.date.copyright | 2012-08-19 | |
dc.date.issued | 2012 | |
dc.date.submitted | 2012-08-10 | |
dc.identifier.citation | [1] S. Ali and M. Shah, 'Floor Fields for Tracking in High Density Crowd Scenes,' Proc. of European Conference on Computer Vision, Marseille, France, Vol. 5303, pp. 1-14, October 2008.
[2] M. R. Anderberg, Cluster Analysis for Applications, 1Ed, New York, NY, USA: Academic Press, 1973. [3] H. Aoyama, K. Ishikawa, J. Seki, M. Okamura, S. Ishimura, and Y. Satsumi, 'Development of Mine Detection Robot System,' International Journal of Advanced Robotic Systems Vol. 4, No. 2, pp. 229-236, 2007. [4] J. Berclaz, F. Fleuret, and P. Fua, 'Robust People Tracking with Global Trajectory Optimization,' Proc. of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), New York, NY, USA, Vol. 1, pp. 744-750, 2006. [5] P. Biber, H. Andreasson, T. Duckett, and A. Schilling, '3D Modeling of Indoor Environments by a Mobile Robot with a Laser Scanner and Panoramic Camera,' Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sendai, Japan, Vol. 4, pp. 3430-3435, 2004. [6] S. S. Blackman, 'Multiple Hypothesis Tracking for Multiple Target Tracking,' IEEE Aerospace and Electronic Systems Magazine, Vol. 19, No. 1, pp. 5-18, 2004. [7] M. Bosse and R. Zlot, 'Map Matching and Data Association for Large-Scale Two-dimensional Laser Scan-based SLAM,' International Journal of Robotics Research, Vol. 27, no. 6, pp. 667-691, 2008. [8] C. L. Breazeal, Designing Sociable Robots, Cambridge, 1Ed, MA, USA: MIT Press, 2002. [9] C. L. Breazeal, 'Socially intelligent robots,' Interactions, Vol. 12, No. 2, pp. 19-22, 2005. [10] S. Candido and S. Hutchinson, 'Minimum Uncertainty Robot Path Planning Using a POMDP Approach,' Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Taipei, Taiwan, pp. 1408-1413, 2010. [11] F. Carreira, T. Canas, A. Silva, and C. Cardeira, 'i-Merc: A Mobile Robot to Deliver Meals inside Health Services,' Proc. of IEEE Conference on Robotics, Automation and Mechatronics (ICRA), Orlando, FL, USA, pp. 1-8, 2006. [12] H. T. Cheng, Algorithms for Partially Observable Markov Decision Processes, Doctoral Dissertation, University of British Columbia, p. 1, 1988. [13] M. Y. Cheng, M.-C. Tsai and C.-Y. Sun, 'Dynamic Visual Tracking Based on Multiple Feature Matching and G–H filter,' Advanced Robotics, Vol. 20, No. 12, pp. 1401-1423, 2006. [14] S. Y. Chung, Spatial Understanding and Motion Planning for a Mobile Robot, Doctoral Dissertation, Department of Mechanical Engineering, National Taiwan University, 2010. [15] S. Y. Chung and H. P. Huang, 'A Mobile Robot that Understands Pedestrian Spatial Behaviors,' Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Taipei, Taiwan, pp. 5861-5866, 2010. [16] C. Cortes and V. Vapnik, 'Support-Vector Networks,' Machine Learning, Vol. 20, No. 3, pp. 273-297, 1995. [17] G. Csurka, C. R. Dance, L. Fan, J. Willamowski, and C. Bray, 'Visual Categorization with Bags of Keypoints,' ECCV International Workshop on Statistical Learning in Computer Vision, Prague, Czech Republic, pp. 1-22, 2004. [18] A. J. Davison, I. D. Reid, N. D. Molton, and O. Stasse, 'MonoSLAM: Real-Time Single Camera SLAM,' IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol. 29, No. 6, pp. 1052-1067, 2007. [19] A. Diaz and J. Ariel, Analysis of Pedestrian Walking Speed for Traffic Engineering Design and Operations, Master Thesis, Department of Civil, Engineering, University of Manitoba, 2008. [20] T. Fong, I. Nourbakhsh, and K. Dautenhahn, 'A survey of socially interactive robots,' Robotics and Autonomous Systems, Vol. 42, No. 3–4, pp. 143-166, 2003. [21] J. A. Goldman, 'Path Planning Problems and Solutions,' Proc. of IEEE National Aerospace and Electronics Conference (NAECON), Dayton, OH, USA, Vol. 1, pp. 105-108, 1994. [22] B. Graf, M. Hans, and R. D. Schraft, 'Care-O-Bot II - Development of a Next Generation Robotic Home Assistant,' Autonomous Robots, Vol. 16, No. 2, pp. 193-205, 2004. [23] R. M. Haralick and L. G. Shapiro, Computer and Robot Vision, Boston, MA, USA: Addison-Wesley Longman Publishing Co., Inc., 1992. [24] D. Helbing and P. Molnár, 'Social Force Model for Pedestrian Dynamics,' Physical Review E, Vol. 51, No. 5, pp. 4282-4286, 1995. [25] C. Heyer, 'Human-robot interaction and future industrial robotics applications,' Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Taipei, Taiwan, pp. 4749-4754, 2010. [26] J. F. Huang, Multi-Robot Exploration with Strictly Limited Communication, Master Thesis, Department of Mechanical Engineering, National Taiwan University, 2010. [27] S. Huang and G. Dissanayake, 'Convergence Analysis for Extended Kalman Filter Based SLAM,' Proc. of IEEE International Conference on Robotics and Automation, Orlando, FL, USA, pp. 412-417, 2006. [28] D. W. Hugh and T. Bailey, “Simultaneous Localization and Mapping (SLAM): Part I The Essential Algorithms,” IEEE Robotics and Automation Magazine, Vol. 13, No. 2, pp. 99-110, 2006. [29] N. Kato and T. Shigetomi, 'Underwater Navigation for Long-Range Autonomous Underwater Vehicles Using Geomagnetic and Bathymetric Information,' Advanced Robotics, Vol. 23, No. 7-8, pp. 787-803. [30] S. Koenig and M. Likhachev, 'D* Lite,' Proc. of AAAI Conference of Artificial Intelligence (AAAI), Edmonton, Canada, pp. 476-783, 2002. [31] B. Lau, K. O. Arras, and W. Burgard, 'Tracking Groups of People with a Multi-model Hypothesis Tracker,' Proc. of IEEE international conference on Robotics and Automation (ICRA), Kobe, Japan, pp. 3487-3492, 2009. [32] C. H. Li, Queuing Model for a Mobile Robot, Master Thesis, Department of Mechanical Engineering, National Taiwan University, 2011. [33] M. Likhachev and D. Ferguson, 'Planning Long Dynamically Feasible Maneuvers for Autonomous Vehicles,' International Journal of Robotics Research, Vol. 28, No. 8, pp. 933-945, 2009. [34] D. G. Lowe, 'Object Recognition from Local Scale-Invariant Features,' Proc. of IEEE International Conference on Computer Vision, Kerkyra, Corfu, Greece, Vol. 2, pp. 1150-1157, 1999. [35] D. G. Lowe, 'Distinctive Image Features from Scale-Invariant Keypoints,' International Journal of Computer Vision, Vol. 60, No. 2, pp. 91-110, 2004. [36] M. Luber, L. Spinello, and K. O. Arras, 'People Tracking in RGB-D Data with On-line Boosted Target Models,' Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Francisco, CA, USA, pp. 3844-3849, 2011. [37] M. Luber, J. A. Stork, G. D. Tipaldi, and K. O. Arras, 'People Tracking with Human Motion Predictions from Social Forces,' Proc. of IEEE International Conference on Robotics and Automation (ICRA) , Anchorage, AK, USA, pp. 464-469, 2010. [38] T. Malisiewicz and A. A. Efros, 'Beyond Categories: The Visual Memex Model for Reasoning about Object Relationships,' Proc. of Neural Information Processing Systems (NIPS), Vancouver, British Columbia, Canada, pp. 1222-1230, 2009. [39] R. Marin, G. Leon, R. Wirz, J. Sales, J. M. Claver, P. J. Sanz, and J. Fernandez, 'Remote Programming of Network Robots Within the UJI Industrial Robotics Telelaboratory: FPGA Vision and SNRP Network Protocol,' IEEE Transactions on Industrial Electronics, Vol. 56, No. 12, pp. 4806-4816, 2009. [40] M. N. Moghadasi, A. T. Haghighat, and S. S. Ghidary, 'Evaluating Markov Decision Process as a Model for Decision Making Under Uncertainty Environment,' Proc. of International Conference on Machine Learning and Cybernetics (ICMLC), Hong Kong, Vol. 5, pp. 2446-2450, 2007. [41] S. d. Moral, D. Pardo, and C. Angulo, 'Social Robot Paradigms: An Overview,' Proc. of the 10th international Work-Conference on Artificial Neural Networks: Part I: Bio-inspired Systems: Computational and Ambient intelligence, Vol. 5517, pp. 773-780, 2009. [42] H. Moravec, 'Sensor Fusion in Certainty Grids for Mobile Robots,' AI Magazine, Vol. 9, No. 2, pp. 61-74, 1988. [43] S. Pellegrini, A. Ess, K. Schindler, and L. van Gool, 'You'll Never Walk Alone: Modeling Social Behavior for Multi-Target Tracking,' Proc. of IEEE International Conference on Computer Vision (ICCV), Kyoto, Japan, pp. 261-268, 2009. [44] J. R. Quinlan, 'Induction of Decision Trees,' Machine Learning, Vol. 1, No. 1, pp. 81-106, 1986. [45] D. Reid, 'An Algorithm for Tracking Multiple Targets,' IEEE Transactions on Automatic Control, Vol. 24, pp. 843-854, 1979. [46] M. Rodriguez, S. Ali, and T. Kanade, 'Tracking in Unstructured Crowded Scenes,' Proc. of IEEE International Conference on Computer Vision (ICCV), Kyoto, Japan, pp. 1389-1396, September 2009. [47] R. D. Sack, 'Human Territoriality: A Theory,' Annals of the Association of American Geographers, Vol. 73, No. 1, pp. 55-74, 1983. [48] R. Siegwart and I. R. Nourbakhsh, Introduction to Autonomous Mobile Robots, 1Ed Cambridge, MA, USA: MIT Press, 2004. [49] M. Y. Shieh, J. C. Hsieh, and C. P. Cheng, 'Design of an Intelligent Hospital Service Robot and Its Applications,' Proc. of IEEE International Conference on Systems, Man and Cybernetics (SMC), Hague, Netherlands, Vol. 5, pp. 4377-4382, 2004. [50] J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, A. Kipman, and A. Blake, 'Real-Time Human Pose Recognition in Parts from Single Depth Images,' Proc. of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, CO, USA, pp. 1297-1304, 2011. [51] S. Thrun, W. Burgard, and D. Fox, Probabilistic Robotics, 1Ed, Cambridge, MA, USA: MIT Press, 2005. [52] N. Tornatis, I. Nourbakhsh, and R. Siegwart, 'Hybrid Simultaneous Localization and Map Building: Closing the Loop with Multi-Hypotheses Tracking,' Proc. of IEEE International Conference on Robotics and Automation (ICRA), Washington, DC, USA, Vol. 3, pp. 2749-2754, 2002. [53] B. Yamauchi, 'Frontier-Based Exploration Using Multiple Robots,' Proc. of the 2nd International Conference on Autonomous Agents (AAMAS), Minneapolis, MN, USA, pp. 47–53, May 1998. [54] C. Yen-Sheng and J. Jih-Gau, 'Intelligent Obstacle Avoidance Control Strategy for Wheeled Mobile Robot,' Proc. of ICCAS-SICE International Joint Conference, Fukuoka, Japan, pp. 3199-3204, 2009. [55] P. N. Yianilos, 'Data Structures and Algorithms for Nearest Neighbor Search in General Metric Spaces,' the fourth annual ACM-SIAM Symposium on Discrete algorithms, Austin, TX, USA, pp. 311-321, 1993. [56] C. Zhou, M. Tan, N. Gu, Z. Cao, S. Wang, and L. Wang, 'The Design and Implementation of a Biomimetic Robot Fish ' International Journal of Advanced Robotic Systems, Vol. 5, pp. 185-192, 2008. [57] D. Zou and P. Tan, 'CoSLAM: Collaborative Visual SLAM in Dynamic Environments,' IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PP, No. 99, pp. 1-1, 2012. [58] Kinect SDK Documentation, Microsoft Corporation, 2012. [59] 'Camera Calibration Toolbox for Matlab,' [Online]. Available: http://www.vision.caltech.edu/bouguetj/calib_doc/. [Accessed: May 20, 2011]. [60] 'Long queues for the 2010 Taipei International Flora Exposition,' [Online]. Available: http://john547.blogspot.com/2010/10/flora-expo.html [Accessed: April 24, 2012]. [61] 'Kinect,” [Online]. Available:http://en.wikipedia.org/wiki/Kinect. [Accessed: May 13, 2012]. [62] 'SICK LMS-291,' [Online]. Available: http://www.pages.drexel.edu/~kws23/tutorials/sick/sick.html. [Accessed: Aug. 13, 2011]. [63] 'OpenCV Wiki,' [Online]. Available: http://opencv.willowgarage.com/wiki/. [Accessed: Aug. 10, 2011]. [64] 'OpenGL Official Website,' [Online]. Available: http://www.opengl.org/. [Accessed: Aug. 10, 2011]. [65] 'Personal Space,' [Online]. Available: http://www.thisplaceis.com/archives/36. [Accessed: April 15, 2012]. [66] 'Webcam,' [Online]. Available: http://www.logitech.com/zh-tw/webcam-communications/webcams/6816. [Accessed: Aug. 13, 2011]. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/6609 | - |
dc.description.abstract | 為了要使得機器人更容易被人們所接受,機器人必須理解環境中的人類行為。在不久的將來,機器人將頻繁出現在人類生活環境中,像是學校、醫院、辦公大樓、博物館、以及一般家庭等等區域。而排隊為人類社會最常見的行為之一,所以機器人要融入人類社會中,排隊就變得非常的重要了。
在這篇論文中,了解人類排隊行為主要針對人與人群之間的相互關係作探討,並提出行人排隊模型,可以幫助機器人檢測以及學習人群效應。之後也探討環境中有那些因素會影響排隊的位置,第一個因素為公車站牌,人類在等待公車時,會站立在公車站牌附近,並有排隊的行為出現。利用SIFT演算法來偵測出公車站牌,並與雷射並用找出公車站牌的位置,最後學習人類等候公車。第二個因素為門,提出了一個演算法可偵測柵格地圖中為門的地方。門對於行人是一個交通要道,當排隊隊伍在門附近的情況時,會有禮貌空出一定範圍的距離讓行人可自由通行,藉由空間效應讓機器人了解這些位置是不可以久留的。 | zh_TW |
dc.description.abstract | We are at the developing stage of service robotics now. Robots provide services for people in the public and home environments. Before that, we need to let robots understand the social behaviors in order to letting robots know how to interact with human correctly. Furthermore, maybe we can achieve the step that robots will cooperate with people and join the coexistence society of humans and robots in the future. The way in which robots are going to live with humans has become an important issue. One of the most common human social behaviors is standing in line. Therefore, to integrate robots into human society, queuing is an important ability.
In this thesis, behavior understanding mainly targets on a queuing task consisting of the interactions between people and the group. A pedestrian queuing model was developed that can help robots to detect and learn crowd effects in human society. I have added the queuing model environment constraint of entrance detection on an occupancy grid map, and bus stop detection. The entrance detection algorithm detects entrances as represented by all kinds of doors and allows the robot to identify the location as a traffic artery with an SSE, thus facilitating robot behavior that is acceptable in human environment. Using the SIFT algorithm makes the identification of bus stops easier to perform. | en |
dc.description.provenance | Made available in DSpace on 2021-05-17T09:15:13Z (GMT). No. of bitstreams: 1 ntu-101-R99522814-1.pdf: 5654884 bytes, checksum: 7e2df2fefae941b36751a906653663c3 (MD5) Previous issue date: 2012 | en |
dc.description.tableofcontents | 誌謝 i
摘要 ii Abstract iii Content iv List of Tables vi List of Figures vii Nomenclature x Chapter 1 Introduction 1 1.1 Relations between Humans and Robots 1 1.2 Objectives and Contributions 4 1.3 Structure of Thesis 6 Chapter 2 Background Knowledge 8 2.1 SLAM and Moving Object Tracking 8 2.1.1 Simultaneous Localization and Mapping 9 2.1.2 Moving Object Tracking 12 2.2 Frontier-based Exploration 15 2.3 Pedestrian Ego Graph (PEG) 17 2.4 Social Navigation 20 Chapter 3 Social Robot Standing in Line Model 27 3.1 Pedestrian Queuing Model 29 3.1.1 Crowd Effect – Distance 29 3.1.2 Crowd Effect – Steering 30 3.1.3 Crowd Effect – Personal Index 31 3.2 Queuing Process 32 3.2.1 A Social Robot Stands in Line 33 3.2.2 Data Collection 34 3.2.3 Recognizing People in Queue 36 3.3 Summary 39 Chapter 4 Standing in Line with Environment Constraints 40 4.1 Introduction 40 4.2 Detection of Environmental Influence Factors 42 4.2.1 Occupancy Grid Map Property 42 4.2.2 Entrance of Free Area Detection 44 4.2.3 Specific Spatial Effect 49 4.3 Image Feature Detection 51 4.3.1 Camera Calibration 51 4.3.2 Bus Stop Detection 54 4.4 Summary 60 Chapter 5 Simulations and Experiments 61 5.1 Software Platform 61 5.2 Hardware Platform 62 5.3 Simulations and Experimental Results 64 5.3.1 Case Study 1: Queuing at a Bus Stop 64 5.3.2 Case Study 2: Queue Guiding in Store 71 5.3.3 Case Study 3: Queuing with SSE Environment Constraint 76 Chapter 6 Conclusions and Future Works 81 6.1 Conclusions 81 6.2 Future Works 82 References 83 | |
dc.language.iso | en | |
dc.title | 行動機器人展示排隊的社會行為 | zh_TW |
dc.title | A Mobile Robot to Demonstrate Social Behavior about Queuing | en |
dc.type | Thesis | |
dc.date.schoolyear | 100-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 林達德(Ta-Te Lin),王傑智(Chieh-Chih Wang) | |
dc.subject.keyword | 排隊,行人排隊模型,人群效應,公車站牌檢測,門檢測, | zh_TW |
dc.subject.keyword | Queuing,Pedestrian Queuing Model,Crowd Effect,Bus Stop Detection,Entrance Detection, | en |
dc.relation.page | 88 | |
dc.rights.note | 同意授權(全球公開) | |
dc.date.accepted | 2012-08-13 | |
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-101-1.pdf | 5.52 MB | Adobe PDF | 檢視/開啟 |
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。