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研究生:徐毓伯
研究生(外文):Yu-Po Hsu
論文名稱:於未知環境中群組機器人合作之類位能場運動路徑規劃
論文名稱(外文):Potential-Field-Like Motion Planning for Multi-Robot Cooperation within Unknown Environment
指導教授:傳立成
指導教授(外文):Li-Chen Fu
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:電機工程學研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2005
畢業學年度:93
語文別:英文
論文頁數:230
中文關鍵詞:行動式載具多群組機器人運動軌跡規劃混合式自動機虛擬力場
外文關鍵詞:Mobile RobotMotion PlanningHybrid AutomatonVirtual Force Field
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本論文發展於未知環境中自動導航的多群組合作機器人系統及建立模型,運動路徑規劃和模型的建立都在此論文中提出。行動式輪型機器人上有影像偵測處理和超音波感測系統,影像系統提供行動式機器人於未知環境中擁有搜索的能力,得以辨識目標物與其相對距離。超音波感測系統提供區域的距離資訊,以利行動式機器人足以在未知環境中行走且不與任何障礙物或其它行動式機器人產生碰撞。另外,每個行動式機器人上都有通訊系統做為信息交換使用,得以使多群組機器人合作完成特定任務。

我們透過混合式系統架構來建立多群組合作機器人系統的模型,混合式自動機描述了連續變數和離散變數隨時間變化的過程,足以建立多群組合作機器人系統所需的模型,包括各機器人間的通訊機制。各機器人運動路徑規劃上,我們使用近似建立位能場的方法來完成導航,所有由感測器上得到或由網路接收到的資訊將被融合進而產生虛擬力場,此虛擬力場將導引行動式機器人於未知環境做自主性的移動。最後,我們透過模擬來測試虛擬力場法則應用於多群組合作機器人系統運動路徑規劃的可行性與效果
This thesis aims to model and develop an autonomous cooperative multi-robot system within unknown environment. Modeling and motion planning algorithm of the cooperative robot system are proposed. Visual sensing system and ultrasonic sensing system are both mounted on the mobile manipulator to extract the spatial information of the environment and to obtain distance information relative to obstacles and other mobile manipulators surrounding it.

We model our cooperative multi-robot system under a hybrid system framework. A hybrid automaton is a dynamic system which describes the evolution in time of the valuations of a set of discrete and continuous variables and is adequate to model the cooperative robot system. Here, virtual force field is used as basic platform for performing the robot motion planning. All the information sensed by the mobile manipulator or received from other mobile robots will produce virtual force fields to guide the mobile robot. Feasibility of this motion planning algorithm is validated via extensive simulations.
摘要 i
ABSTRACT ii
Contents I
List of Figure V
List of Table XII
Chapter 1 1
Introduction 1
1.1 Preface 1
1.2 Background 2
1.2.1 Vision System 3
1.2.2 Modeling of Cooperative Robotics 4
1.2.3 Intelligent Robot Navigation 6
1.3 Problem Statement 8
1.4 Motivation and Contributions 8
1.5 Organization of This Thesis 12
Chapter 2 13
Preliminary 13
2.1 Architecture of the Mobile Manipulator System 13
2.2 Robot Kinematics Model 16
2.3 Coordinate Transformation 19
2.4 Fundamental Digital Image Processing 25
2.4.1 Color Image and Gray Scale Image 25
2.4.2 Thresholding 27
2.4.3 Temporal Differencing 27
2.4.4 Gaussian Filtering 29
2.4.5 Edge Detection 31
2.4.6 Template Matching 33
Chapter 3 37
Visual Sensing System 37
3.1 Visual Tracking System 38
3.1.1 Object Detection 39
3.1.2 Hausdorff Algorithm 43
3.1.2.1 Hausdorff Distance 43
3.1.2.2 Distance Transform 49
3.1.3 Visual Tracking 51
3.2 Vision-Based Location Estimation 53
3.2.1 Location Problem 53
3.2.2 Camera Configuration 54
3.2.3 Transformation Formulation 56
3.3 Laser Range Finder 60
Chapter 4 63
System Modeling 63
4.1 Hybrid Systems 63
4.1.1 Overview 63
4.1.2 Hybrid Automata 64
4.2 Modeling of Cooperative Robotics 68
4.2.1 Model of the Multi-Robot System 68
4.2.2 Supervisory Design 69
4.3 Discussion of Theory Completeness 85
4.3.1 Zero Force Field in Wandering State 85
4.3.2 Accidental Collision 86
4.3.3 Collision among Robots 86
4.3.4 Stability of Communication Channel 87
4.3.5 Space behind Mobile Robot 87
4.3.6 Robot Formation Assumption 88
4.3.7 Caging without Facing Target Object 88
4.3.8 Laser System in Finely-tune State 88
Chapter 5 91
Sensor-Based Force Field Approach 91
5.1 Conventional Potential Field Approach 91
5.1.1 Attractive Potential Field 93
5.1.2 Repulsive Potential Field 93
5.1.3 Local Minima Problem 95
5.2 State Dependent Artificial Force Field 97
5.2.1 Searching 97
5.2.1.1 Wandering State 97
5.2.1.2 Obstacle Avoidance and Virtual Attractive Force 100
5.2.1.3 Reverse1 State 106
5.2.1.4 Discussion 108
5.2.2 Formation 110
5.2.2.1 GoToLocation State 110
5.2.2.2 GoToArea State 114
5.2.2.3 Formation_master State 118
5.2.2.4 Group Morphology Formation 119
5.2.2.5 Formation_slave State 122
5.2.2.6 Avoid State 126
5.2.2.7 Discussion 128
5.2.3 Caging 129
5.2.3.1 Approach State 129
5.2.3.2 Roughly-tune State 132
5.2.3.3 Finely-tune State 132
5.2.3.4 Discussion 133
5.2.4 Transportation 134
5.2.4.1 Reverse States 134
5.2.4.2 Transportation State 135
5.2.4.3 Wait States 135
5.2.4.4 Grasp State 136
5.2.4.5 Park State 137
5.2.4.6 End State 137
Chapter 6 139
Simulations 139
6.1 Simulator and Simulation Setup 139
6.1.1 Webots 139
6.1.2 Mobile Manipulator Construction 141
6.2 Wandering with Obstacle Avoidance 143
6.2.1 Collision Avoidance 143
6.2.2 Backtracking Mechanism 148
6.3 Deadlock Situation 151
6.4 Searching for Target Object 153
6.5 Robot Team Cage Target Object 156
6.5.1 Individual Formation Position Estimation 156
6.5.2 Formation by N Robots 159
6.5.3 Formation with Robot Collision May Occur 163
6.6 Robot Team Approach Target Object 167
6.6.1 Approach Target Object Directly 167
6.6.2 Approach Target Object after Formation 170
Chapter 7 175
Experimental Results 175
7.1 Experimental Setup 175
7.1.1 Hardware of the Experimental System (Treasure Hunter) 175
7.1.2 Hardware of the Experimental System (Pioneer) 176
7.1.2 Software of the Experimental System 178
7.2 Experimental Visual System 180
7.2.1 Depth Estimation 181
7.2.2 Downsampling Template 185
7.2.3 Template Matching 188
7.2.4 Visual Tracking 189
7.3 Robot Experiments 192
7.3.1 Wander in Environment 192
7.3.2 Obstacle Avoidance 196
7.3.3 Backtracking Mechanism 199
7.3.4 Target Searching 204
7.3.5 Robot Formation 209
7.3.6 Laser Range Finder 214
Chapter 8 219
Conclusions and Future Work 219
8.1 Conclusions 219
8.2 Future Work 221
References 223
[1]C. Barret, M. Benreguieg, and H. Maaref, “Fuzzy Agents for Reactive Navigation of a Mobile Robot,” in the First International Conference on Knowledge-Based Intelligent Electronic Systems, pp. 649 –658, 1997.
[2]S. Waydo, and R. M. Murray, “Vehicle Motion Planning Using Stream Functions,” in Proceedings of the IEEE International Conference on Robotics and Automation, Vol. 2, pp. 2484-2491, 2003.
[3]T. Hu and S. X. Yang, “Real-time Torque Control of Nonholonomic Mobile Robots with Obstacle Avoidance,” in Proceedings of the IEEE International Symposium on Intelligent Control Vancouver, pp. 81-86, 2002.
[4] G. Bianco and P. Fiorini, “Visual Avoidance of Moving Obstacles Based on Vector Field Disturbances,” in Proceedings of the IEEE International Conference on Robotics & Automation, Vol. 3, pp. 2704-2709, 2001.
[5] T. Arai and J. Ota, “Let us Work Together -Task Planning of Multiple Mobile Robots-,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Vol. 1, pp. 298-303, 1996.
[6] O. M. AI-Jarrah and Y. F. Zheng, “Arm-Manipulator Coordination for Load Sharing using Variable Compliance Control”, in Proceedings of the IEEE International Conference on Robotics and Automation, Vol. 1, pp.895-900, 1997.


[7] D. Fox, W. Burgard, H. Kruppa, and S. Thrun, “A Probabilistic Approach to Collaborative Multi-robot Localization,” in Special Issue of Autonomous Robots on Heterogeneous Multi-Robot Systems, Vol. 8, No. 3, pp. 325–344, 2000.
[8] J. Feddema and D. Schoenwald, “Decentralized Control of Cooperative Robotic Vehicles,” in Proceedings of SPIE, Vol. 4364, 2001.
[9] J. S. Jennings, G. Whelan, and W. F. Evans, “Cooperative Search and Rescue with a Team of Mobile Robots,” in Proceedings of the IEEE International Conference of Advanced Robotics, pp. 193–200, 1997.
[10]C. H. Chiu Huang, “Localization and Map-Building Using Multi-Robot Cooperative Sensing,” Department of Electrical and Control Engineering, National Chiao Tung University, Master’s Thesis, 2003.
[11]D. Rus, B. Donald, and J. Jennings, “Moving Furniture with Teams of Autonomous Robots,” in Proceedings of the IEEE/RSJ International Conference of Intelligent Robots and Systems, Vol. 1, pp. 235–242, 1995.
[12]M. Mataric, M. Nilsson, and K. Simsarian, “Cooperative Multi-robot Box Pushing,” in Proceedings of the IEEE/RSJ International Conference of Intelligent Robots and Systems, Vol. 3, pp. 556–561, 1995.
[13]D. Stilwell and J. Bay, “Toward the Development of a Material Transport System using Swarms of Ant-like Robots,” in Proceedings of the IEEE International Conference Robotics and Automation, Vol.1, pp. 766–771, 1993.
[14]L. E. Parker, G. Bekey, and J. Barhen, “Current State of The Art in Distributed Autonomous Mobile Robotics,” in Distributed Autonomous Robotics Systems, Vol. 4, pp. 3-12, 2000.


[15]G. A. S. Pereira, B. S. Pimentel, L. Chaimowicz, and M. F. M. Campos, “Coordination of Multiple Mobile Robots in an Object Carrying Task using Implicit Communication,” in Proceedings of the IEEE International Conference on Robotics and Automation, Vol. 1, pp. 281-286, 2002.
[16]D. Goldberg, and M. J. Mataric, “Coordinating Mobile Robot Group Behavior using a Model of Interaction Dynamics,” in Proceedings of the Agents-99, pp. 100-107, 1999.
[17]Y. Hirata, and K. Kosuge, “Distributed Robot Helpers Handling a Single Object in Cooperation with a Human,” in Proceedings of the IEEE International Conference on Robotics and Automation, Vol. 1, pp. 458-463, 2000.
[18]A. K. Das, R. Fierro, V. Kumar, B. Southall, J. Spletzer, and C. J. Taylor, “Real-Time Vision-Based Control of a Nonholonmic Mobile Robot,” in Proceedings of the IEEE International Conference on Robotics and Automation, Vol. 2 , pp. 1714-1719, 2001.
[19]E. M. Petriu, “Automated Guided Vehicle with Absolute Encoded Guide-path,” in the IEEE Transactions on Robotics and Automation, Vol. 7, No.4, pp.562-565, 1991.
[20]S. Soatto, R. Frezza, and P. Perona, “Motion Estimation via Dynamic Vision,” in the IEEE Transactions on Automatic Control, Vol. 41, pp. 393–413, 1996.
[21]G. Beccari, S. Caselli, F. Zanichelli and A. Calafiore, “Vision-based Line Tracking and Navigation in Structured Environments,” in the IEEE Computational Intelligence in Robotics and Automation, pp. 406-411, 1997.
[22]J. Chen, W. E. Dixon, D. M. Dawson, and M. Mcintire, “Homography-Based Visual Servo Tracking Control of a Wheeled Mobile Robot,” in Proceedings of the IEEE/RSJ International Conference of Intelligent Robots and Systems, Vol. 2, pp. 1814-1819, 1997

[23]C. J. Taylor, J. Kosecka, R. Blasi, and J. Malik, “A Comparative Study of Vision-Based Lateral Control Strategies for Autonomous Highway Driving,” in the International Journal Robotic Research, Vol. 18, No. 5, pp. 442-453, 1999.
[24]Y. Ma, J. Kosecka, and S. S. Sastry, “Vision Guided Navigation for a Nonholonomic Mobile Robot,” in the IEEE Transaction on Robotics and Automation, Vol. 15, No. 3, pp. 521-536, 1999.
[25]Y. Yagi, H. Nagai, K.Yamazawa and M. Yachida, “Reactive Visual Navigation Based on Omnidirectional Sensing-path Following and Collision Avoidance,” in Proceedings of the IEEE/RSJ International Conference of Intelligent Robots and Systems, Vol. 1, pp.58-63, 1999.
[26]C. R. Kube and H. Zhang, “Task modeling in collective robotics,” in Autonomous Robots, pp. 53-72, 1997.
[27]R. Alur, A. Das, J. Esposito, R. Fierro, G. Grudic, Y. Hur, V. Kumar, I. Lee, J. strowske, G. appas, B. Southall, J. Spletzer, and C. Taylor, “A Framework and Architecture for Multirobot Coordination,” in the International Journal of Robotics Research, Vol. 21, pp. 977-995, 2002.
[28]M. Egerstedt, and X. Hu, “A Hybrid Control Approach to Action Coordination for Mobile Robots”, in Automatica, Vol. 38, pp. 125-130, 2002.
[29]D. Milutinovic, an d P. Lima, “Petri Net Models of Robotic Tasks,” in Proceedings of the IEEE International Conference on Robotics and Automation, Vol. 4, pp. 4059-4064, 2002.
[30] R. R. MURPHY, Introduction to AI Robotics, London: The MIT Press, 2000.
[31]Y. K. Hwang, and N. Ahuja, “A Potential Field Approach to Path Planning,” in IEEE Transactions on Robotics and Automation, Vol. 8, No.1, pp.23-32, 1992.

[32]A. Zhu, and S. X. Yang, “A Fuzzy Logic Approach to Reactive Navigation of Behavior-Based Mobile Robots,” in Proceedings of the IEEE International Conference on Robotics and Automation, Vol. 5, pp. 5045-5050, 2004.
[33]0. Khatib, “Real-Time Obstacle Avoidance for Manipulators and Mobile Robots,” in the international Journal of Robotics Research, Vol. 5, pp. 90-98, 1986.
[34]J. 0. Kim, and P.K. Khosla, “Real-Time Obstacle Avoidance using Harmonic Potential Functions,” in the IEEE Transaction on Robotics and Automation, Vol. 8, pp. 338-349, 1992.
[35]W. K. Pratt, Digital Image Processing, 3rd Edition, United States of America: Wiley Inc., 2001.
[36]M. M Richard, Z. Li, and S. S. Sastry, “A Mathematical Introduction to Robotic Manipulation,” CRC Press Inc, 1994.
[37]R. M. Haralick, and L. G. Shapiro, Computer and Robot Vision, Vol. 1, Addison-Wesley Inc., 1992.
[38]S. Yalamanchili, W. N. Martin, and J. K. Aggarwal, “Extraction of Moving Object Description via Differencing,” in CGIP, Vol. 18, pp. 188-201, 1982.
[39]C. C. Wang, “Driver Assistance System for Lane Departure Prevention and Collision Avoidance with Night Vision,” Department of Computer Science and Information Engineering, National Taiwan University, Master’s Thesis, 2004.
[40]R. Brunelli, and T. Poggio, “Template Matching: Matched Spatial Filters and Beyond,” MIT AI Memo 1549, July 1995.
[41]M. S. Lew, N. Sube, and T. S. Huang, “Improving Visual Matching,” in the IEEE Conference on Computer Vision and Pattern Recognition, Vol. 2, pp. 58 –65, 2000.

[42] J. P. Lewis, “Fast Normalized Cross-Correlation,” in Vision Interface, 1995.
[43]Y. S. Chen, Y. P. Hung, and C. S. Fuh, “A Fast Block Matching Algorithm Based on the Winner-Update Strategy,” in proceeding of the 4th Asian Conference on Computer Vision, Vol. 2, pp. 977-982, 2000.
[44]A. M. Peacock, S. Matsunaga, D. Renshaw, J. Hannah, and A. Murray, “Reference Block Updating When Tracking with Block Matching Algorithm,” Electronics letters 17th, Vol. 36, No.34, pp. 309-310, 2000.
[45]C. Haworth, A. M. Peacock, and D. Renshaw, “Performance of Reference Block Updating Techniques when Tracking with the Block Matching Algorithm,” in Proceedings of the International Conference of the Image Processing, Vol. 1, pp.365-368, 2001.
[46]A. Lipton, H. Fujiyoshi, and R. Patil, “Moving Target Classification and Tracking from Real-Time Video,” in Proceedings of the DARPA Image Understanding Workshop, 1998
[47]Z. T. Sun, “On-Road Computer-Vision Based Obstacle Avoidance,” Department of Computer Science and Information Engineering, National Taiwan University, Master’s Thesis, 2000.
[48]W. C. Hsieh, “Vision Based Obstacle Warning System for On-Road Driving,” Department of Computer Science and Information Engineering, National Taiwan University, Master’s Thesis, 2001.
[49]Y. I. Abdel-Aziz, and H. M. Karara, “Direct Linear Transformation from Comparator Coordinates into Object Space Coordinates in Close-Range Photogrammetry,” in Proceedings of the Symposium on Close-Range Photogrametry, pp. 1-18, 1971.
[50]T. Echingo, “A Camera Calibration Technique Using Three Sets of Parallel Lines,” Machine Vision and Applications, Vol. 3, pp. 159-167, 1990.
[51]L. L. Wang, and W. Tsai, “Camera Calibration by Vanishing Lines for 3-D Computer Vision,” in the IEEE Transactions on Pattern Analysis and Machine Intelligence, Vo1. 13, No. 4, pp. 370-376, 1991.
[52]C. M. Ozvern and A. S. Willsky, ”Output Stabilizability of Discrete Event Dynamic Systems,” in the IEEE Transaction on Automatic Control, Vol. 36, No. 8, 1991.
[53]K. M. Passino, A. N. Michel, and P. J. Antsaklis, “Lyapunov Stability of a Class of Discrete Event Systems,” in the IEEE Transaction Automatic Control, Vol. 39, No. 2, 1994.
[54]J. Lyeros, K. H. Johansson, S. N. Simic, J. Zhang and S. S. Sastry, “Dynamical Properties of Hybrid Automata,” in the IEEE Transaction Automatic Control, Vol. 48, No. 1, 2003.
[55]L. Chaimowicz, “Dynamic Coordination of Cooperative Robots: A Hybrid Systems Approach,” Ph.D thesis, Federal University of Minas Gerais, June 2002.
[56]R. Siegwart and I. R. Nourbakhsh, Introduction to Autonomous Mobile Robots, London: The MIT Press, 2004.
[57]P. Song, and V. Kumar, “A Potential Field Based Approach to Multi-Robot Manipulation,” in Proceedings of the IEEE International Conference on Robotics and Automation, pp. 870-876, 2002.
[58] Cyberbotics Ltd., http://www.cyberbotics.com/
[59]D. J. Tzou, “A Hybrid System Approach for Cooperative Control of Mobile Manipulators,” Department of Electrical Engineering, National Taiwan University, Master’s Thesis, 2005.
[60]Pioneer3 & Pioneer2, H8-Series Operations Manual, ActivMedia Robotics, 19 Columbia Drive Amherst, NH 03031.
[61]M. Y. Yu, “Bandwidth Control Based on Wireless LAN for Applications in Multi-robot Cooperative System,” Department of Electrical Engineering, National Taiwan University, Master’s Thesis, 2005.
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