多机器人编队群集运动控制的研究
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摘要
近年来,多机器人运动规划问题渐渐成为机器人学中研究的热点问题。多机器人的运动规划主要包括避障避碰、群集运动、编队控制三种控制行为。多机器人的群集控制要使整个机器人队伍具有分离性、队列性和凝聚性;而多机器人的编队控制要使一队机器人在运动时保持一个期望的队形,并为系统提供冗余性和结构的灵活性。本文主要是基于图论和人工势场理论对多机器人的编队群集运动开展了进一步的研究。
论文首先对国内外学术界关于多机器人运动规划(包括避障规划、编队控制,群集运动控制)的研究工作进行了综述,并把综述的重点放在多机器人编队控制的问题上。
其次,对图论进行了概述,并对应用图论的文献进行了归纳总结,然后详细介绍了图论和人工势场法相结合的多机器人编队方法。接着对基于图论和人工势场法的多机器人群集控制方法进行了改进,使之能够使多机器人在群集运动的同时形成预定的队形,然后对改进的方法证明了其稳定性。
再次,通过对已有的减少通信方法的分析,并基于图论和人工势场理论,提出了一种改进的编队群集运动控制律,它能明显的减少机器人间的通信量,使多机器人系统可以适应一些对通信量有严格要求的环境。
最后,对论文中提出的一些结论和文献综述中提到的一些控制方法进行了一系列的仿真实验,并对仿真结果进行了分析。实验结果表明了本论文研究的基于图论和人工势场理论的多机器人编队群集控制和减少通信量的控制规则的可行性和有效性。
Motion planning of multiple robots is becoming a hot topic in robot field in recent years. Motion planning of multiple robots includes obstacle avoidance (collision avoidance), flocking and formation control. Flocking control makes the group of robots have the characteristics of separation, alignment and cohesion. Formation control makes a robot team maintain a desired formation and provide redundancy and structural flexibility. The formation and flocking control based on graph theory and artificial potential field method (APF) is further researched in this thesis.
This thesis firstly made a summary of the motion planning (included obstacle avoidance, flocking and formation control) in domestic and foreign academic filed, and focused on formation control issues of multiple robots.
Secondly, the outline and application of graph theory are summarized. The formation control based on graph theory and APF is detailedly introduced. The flocking control based on graph theory and APF is improve to make the multiple robots reach a desired formation, at the same time the stability of the improved method has been proved.
Thirdly, through the analysis of the method of reducing the communications, an improved formation and flocking control law based on graph theory and APF is presented to reduce the communications among multiple robots, and make the multiple robots system adapt to the environment which has strict requests for traffic.
At last, simulations are presented about some conclusions and control laws in literature, and the results are analyzed. The results of simulations demonstrate the feasibility and validity of formation and flocking control law (based on graph theory and APF) and the control law of reducing communications.
论文首先对国内外学术界关于多机器人运动规划(包括避障规划、编队控制,群集运动控制)的研究工作进行了综述,并把综述的重点放在多机器人编队控制的问题上。
其次,对图论进行了概述,并对应用图论的文献进行了归纳总结,然后详细介绍了图论和人工势场法相结合的多机器人编队方法。接着对基于图论和人工势场法的多机器人群集控制方法进行了改进,使之能够使多机器人在群集运动的同时形成预定的队形,然后对改进的方法证明了其稳定性。
再次,通过对已有的减少通信方法的分析,并基于图论和人工势场理论,提出了一种改进的编队群集运动控制律,它能明显的减少机器人间的通信量,使多机器人系统可以适应一些对通信量有严格要求的环境。
最后,对论文中提出的一些结论和文献综述中提到的一些控制方法进行了一系列的仿真实验,并对仿真结果进行了分析。实验结果表明了本论文研究的基于图论和人工势场理论的多机器人编队群集控制和减少通信量的控制规则的可行性和有效性。
Motion planning of multiple robots is becoming a hot topic in robot field in recent years. Motion planning of multiple robots includes obstacle avoidance (collision avoidance), flocking and formation control. Flocking control makes the group of robots have the characteristics of separation, alignment and cohesion. Formation control makes a robot team maintain a desired formation and provide redundancy and structural flexibility. The formation and flocking control based on graph theory and artificial potential field method (APF) is further researched in this thesis.
This thesis firstly made a summary of the motion planning (included obstacle avoidance, flocking and formation control) in domestic and foreign academic filed, and focused on formation control issues of multiple robots.
Secondly, the outline and application of graph theory are summarized. The formation control based on graph theory and APF is detailedly introduced. The flocking control based on graph theory and APF is improve to make the multiple robots reach a desired formation, at the same time the stability of the improved method has been proved.
Thirdly, through the analysis of the method of reducing the communications, an improved formation and flocking control law based on graph theory and APF is presented to reduce the communications among multiple robots, and make the multiple robots system adapt to the environment which has strict requests for traffic.
At last, simulations are presented about some conclusions and control laws in literature, and the results are analyzed. The results of simulations demonstrate the feasibility and validity of formation and flocking control law (based on graph theory and APF) and the control law of reducing communications.
引文
[1]谭民,王硕等.多机器人系统.北京:清华大学出版社, 2005. 6~27
[2]谭民,范永,徐国华.机器人群体协作与控制的研究.机器人, 2001, 23(2):178~182
[3] Cao Y. U, Fukunaga A. S, Kahng A. B. Cooperative Mobile Robotics: Antecedents and Directions. Autonomous Robots, 1997, 4(1):7~27
[4] Borenstein J, Koren Y. Real-time Obstacle Avoidance for Fast Mobile Robots. IEEE Transactions on Systems, 1989, 19(5):1179~1187.
[5] Zalama E. A Real-time, Unsupervised Neural Network for the Low-level Control of a Mobile Robot in a Nonstationary Environment. Neural Networks, 1995, 8(1):103~123
[6] Fiorini P, Shiller Z. Motion Planning in Dynamic Environments Using the Relative Velocity Paradigm. in: Proceedings of IEEE International Conference on Robotics and Automation. Atlanta, GA, 1993. 560~565
[7] Waydo S,Murray R. M. Vehicle Motion Planning Using Stream Functions. in: Proceedings of IEEE International Conference on Robotics and Automation. Taipei, 2003. 2484~2491
[8] Kato S, Nishiyama S, Takeno J. Coordinating Mobile Robots by Applying Traffic Rules. in: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. Raleigh, 1992. 1535~1541
[9] Khatib O. Real-time Obstacle Avoidance for Manipulators and Mobile Robots. in: Proceedings of IEEE International Conference on Robotics and Automation. Missouri, 1985. 500~505
[10]陈宁.智能体机器人动态路径规划研究: [硕士学位论文].武汉:华中科技大学图书馆, 2004
[11]巍然.基于人工势场理论的多移动机器人协同控制研究: [硕士学位论文].武汉:华中科技大学图书馆, 2006
[12] Kim D. H, Wang H. O, Guohua Ye, et al. Decentralized Control of AutonomousSwarm Systems Using Artificial Potential Functions: Analytical Design Guidelines. in: Proceedings of the 2004 IEEE Conference on Decision and Control. Nassau, Bahamas, 2004. 159~164
[13]赵凤花.多移动机器人运动协调中避障的研究: [硕士学位论文].武汉:华中科技大学图书馆, 2006
[14]程磊.多移动机器人协调控制系统的研究与实现: [博士学位论文].武汉:华中科技大学图书馆, 2006
[15]任德华,卢桂章.对队形控制的思考.控制与决策, 2005, 20(6):601~606
[16] Chen YangQuan, Wang Zhongmin. Formation Control: A Review and A New Consideration. in: Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. Edmonton, Canada, 2005. 3181~3186
[17] Desai J. P, Ostrowski J, Kumar V. Controlling Formations of Multiple Mobile Robots. in: Proceedings of IEEE International Conference on Robotics and Automation. Leuven, Belgium, 1998. 2864~2869
[18] Takahashi H, Nishi H, Ohnishi K. Autonomous Decentralized Control for Formation of Multiple Mobile Robots Considering Ability of Robot. IEEE Transactions on Industrial Electronics, 2004, 51(6):1272~1279
[19] Shao Jinyan, Xie Guangming, Yu Junzhi, et al. A Tracking Controller for Motion Coordination of Multiple Mobile Robots. in: Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. Edmonton, Canada, 2005. 783~788
[20] Beard R. W, Lawton J, Hadaegh F. Y. A Feedback Architecture for Formation Control. in: Proceedings of the American Control Conference. Phoenix, Arizona, 2000. 4087~4091
[21] Beard R.W, Lawton J, Hadaegh F. Y. A Coordination Architecture for Spacecraft Formation Control. IEEE Transactions on Control Systems Technology, 2001, 9(6):777~790
[22] Wei Ren, Beard R.W. A Decentralized Scheme for Spacecraft Formation Flying via the Virtual Structure Approach. in: Proceedings of the 2003 American Controlconference. Denver, Colorado, 2003. 1746~1751
[23] Balch T, Arkin R. C. Behavior-based Formation Control for Multi Robot Teams. IEEE Transactions on Robotics and Automation, 1998, 14(6):926~939
[24] Cao Zhiqiang, Xie Liangjun, Zhang Bin. Formation Constrained Multi-robot System in Unknown Environments. in: Proceedings of IEEE International Conference on Robotics and Automation. Taipei, 2003. 735~740
[25] Cao Zhiqiang, Tan Min, Wang Shuo, et al. The Optimization Research of Formation Control for Multiple Mobile Robots. in: Proceedings of the 4th World Congress on Intelligent Control and Automation. Shanghai, 2002. 1270~1274
[26] Dudenhoeffer D. D, Jones M. P. A Formation Behavior for Large-scale Micro-robot Force Deployment. in: Proceedings of Simulation Conference. Vancouver, 2000. 972~982
[27] Monteiro S, Bicho E. A Dynamical Systems Approach to Behavior-based Formation control. in: Proceedings of IEEE International Conference on Robotics and Automation. Washington DC, 2002. 2606~2611
[28] Ge S. S, Fua C. H, Liew W. M. Swarm Formations Using the Ggeneral Gormation Potential Function. in: Proceedings of the 2004 IEEE Conference on Automation and Mechatronics. Singapore, 2004. 655~660
[29] Leonard N. E, Fiorelli E. Virtual Leader, Artificial Potentials and Coordinated Control of Groups. in: Proceedings of the 40th IEEE Conference on Decision and Control. Orlando, Florida, 2001. 2968~2973
[30] Xi Xiaorui, Abed E. H. Formation Control with Virtual Leaders and Reduced Communications. in: Proceedings of the 44th IEEE Conference on Decision and Control. Seville, Spain, 2005. 1854~1860
[31] Baras J. S, Tan Xiaobo, Hovareshti P. Decentralized Control of Autonomous Vehicles. in: Proceedings of the 42nd IEEE Conference on Decision and Control. Maui, Hawaii, 2003. 1532~1537
[32] Pereira G. A. S, Das A. K, Campos M. F. M. Formation Control with Configuration Space Constraints. in: Proceedings of the 2003 IEEE/RSJ International Conferenceon Robots and Intelligent Systems. Las Vegas, Nevada, 2003. 2755~2760
[33] Ge S. S, Fua C. H. Queues and Artificial Potential Trenches for Multirobot Formations. IEEE Transactions on Robotics, 2005, 21(4):646~656
[34] Reynolds. Flocks, herds, and schools: A Distributed Behavioral Model. Computer Graphics, 1987, 21(4):25~34
[35] Wang Long, Shi Hong, Chu Tianguang. Flocking Control of Groups of Mobile Autonomous Agents via Local Feedback. in: Proceedings of the 2005 IEEE International Conference on Control and Automation. Barcelona, Spain, 2005. 441~446
[36]徐俊明.图论及其应用.第二版.合肥:中国科学技术大学出版社, 2004. 1~43
[37] Fax J. A, Murray R. M. Information Flow and Cooperative Control of Vehicle Formations. IEEE Transactions on Automatic Control, 2004, 49(9):1465~1476
[38] Lafferriere G, Caughman J, Williams A. Graph Theoretic Methods in the Stability of Vehicle Formations. in Proceedings of the American Control Conference. Boston, Massachusetts, 2004. 3729~3734.
[39] Olfati-Saber R, Murray R. M. Distributed Cooperative Control of Multiple Vehicle Formations Using Structural Potential Functions. in: Proceedings of the 15th IFAC World Congress. Barcelona, 2002. 454~459
[40]贾秋玲,闫建国,王新民.基于势函数的多机器人系统的编队控制.机器人, 2006, 28(2):111~114
[41]杨克劭,包学游.矩阵分析.哈尔滨:哈尔滨工业大学出版社, 1995. 89~93
[42] Das S. M, Hu Y. Charlie, Lee C. S. G. Supporting Many-to-One Communication in Mobile Multi-Robot Ad Hoc Sensing Networks. in: Proceedings of the 2004 IEEE International Conference on Robotics and Automation. New Orleans, LA, 2004. 659~664
[43] Chen Z. D, Kung H. T, Vlah D. Ad Hoc Relay Wireless Networks over Moving Vehicles on Highways. in: Proceedings of ACM Symposium on MobiHoc, California, 2001. 247~250
[44] Das S. M, Hu Y. C, Lee C. S. G, et al. An Efficient Group Communication Protocolfor Mobile Robots. in: Proceedings of the 2005 IEEE International Conference on Robotics and Automation. Barcelona, 2005. 87~92
[2]谭民,范永,徐国华.机器人群体协作与控制的研究.机器人, 2001, 23(2):178~182
[3] Cao Y. U, Fukunaga A. S, Kahng A. B. Cooperative Mobile Robotics: Antecedents and Directions. Autonomous Robots, 1997, 4(1):7~27
[4] Borenstein J, Koren Y. Real-time Obstacle Avoidance for Fast Mobile Robots. IEEE Transactions on Systems, 1989, 19(5):1179~1187.
[5] Zalama E. A Real-time, Unsupervised Neural Network for the Low-level Control of a Mobile Robot in a Nonstationary Environment. Neural Networks, 1995, 8(1):103~123
[6] Fiorini P, Shiller Z. Motion Planning in Dynamic Environments Using the Relative Velocity Paradigm. in: Proceedings of IEEE International Conference on Robotics and Automation. Atlanta, GA, 1993. 560~565
[7] Waydo S,Murray R. M. Vehicle Motion Planning Using Stream Functions. in: Proceedings of IEEE International Conference on Robotics and Automation. Taipei, 2003. 2484~2491
[8] Kato S, Nishiyama S, Takeno J. Coordinating Mobile Robots by Applying Traffic Rules. in: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. Raleigh, 1992. 1535~1541
[9] Khatib O. Real-time Obstacle Avoidance for Manipulators and Mobile Robots. in: Proceedings of IEEE International Conference on Robotics and Automation. Missouri, 1985. 500~505
[10]陈宁.智能体机器人动态路径规划研究: [硕士学位论文].武汉:华中科技大学图书馆, 2004
[11]巍然.基于人工势场理论的多移动机器人协同控制研究: [硕士学位论文].武汉:华中科技大学图书馆, 2006
[12] Kim D. H, Wang H. O, Guohua Ye, et al. Decentralized Control of AutonomousSwarm Systems Using Artificial Potential Functions: Analytical Design Guidelines. in: Proceedings of the 2004 IEEE Conference on Decision and Control. Nassau, Bahamas, 2004. 159~164
[13]赵凤花.多移动机器人运动协调中避障的研究: [硕士学位论文].武汉:华中科技大学图书馆, 2006
[14]程磊.多移动机器人协调控制系统的研究与实现: [博士学位论文].武汉:华中科技大学图书馆, 2006
[15]任德华,卢桂章.对队形控制的思考.控制与决策, 2005, 20(6):601~606
[16] Chen YangQuan, Wang Zhongmin. Formation Control: A Review and A New Consideration. in: Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. Edmonton, Canada, 2005. 3181~3186
[17] Desai J. P, Ostrowski J, Kumar V. Controlling Formations of Multiple Mobile Robots. in: Proceedings of IEEE International Conference on Robotics and Automation. Leuven, Belgium, 1998. 2864~2869
[18] Takahashi H, Nishi H, Ohnishi K. Autonomous Decentralized Control for Formation of Multiple Mobile Robots Considering Ability of Robot. IEEE Transactions on Industrial Electronics, 2004, 51(6):1272~1279
[19] Shao Jinyan, Xie Guangming, Yu Junzhi, et al. A Tracking Controller for Motion Coordination of Multiple Mobile Robots. in: Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. Edmonton, Canada, 2005. 783~788
[20] Beard R. W, Lawton J, Hadaegh F. Y. A Feedback Architecture for Formation Control. in: Proceedings of the American Control Conference. Phoenix, Arizona, 2000. 4087~4091
[21] Beard R.W, Lawton J, Hadaegh F. Y. A Coordination Architecture for Spacecraft Formation Control. IEEE Transactions on Control Systems Technology, 2001, 9(6):777~790
[22] Wei Ren, Beard R.W. A Decentralized Scheme for Spacecraft Formation Flying via the Virtual Structure Approach. in: Proceedings of the 2003 American Controlconference. Denver, Colorado, 2003. 1746~1751
[23] Balch T, Arkin R. C. Behavior-based Formation Control for Multi Robot Teams. IEEE Transactions on Robotics and Automation, 1998, 14(6):926~939
[24] Cao Zhiqiang, Xie Liangjun, Zhang Bin. Formation Constrained Multi-robot System in Unknown Environments. in: Proceedings of IEEE International Conference on Robotics and Automation. Taipei, 2003. 735~740
[25] Cao Zhiqiang, Tan Min, Wang Shuo, et al. The Optimization Research of Formation Control for Multiple Mobile Robots. in: Proceedings of the 4th World Congress on Intelligent Control and Automation. Shanghai, 2002. 1270~1274
[26] Dudenhoeffer D. D, Jones M. P. A Formation Behavior for Large-scale Micro-robot Force Deployment. in: Proceedings of Simulation Conference. Vancouver, 2000. 972~982
[27] Monteiro S, Bicho E. A Dynamical Systems Approach to Behavior-based Formation control. in: Proceedings of IEEE International Conference on Robotics and Automation. Washington DC, 2002. 2606~2611
[28] Ge S. S, Fua C. H, Liew W. M. Swarm Formations Using the Ggeneral Gormation Potential Function. in: Proceedings of the 2004 IEEE Conference on Automation and Mechatronics. Singapore, 2004. 655~660
[29] Leonard N. E, Fiorelli E. Virtual Leader, Artificial Potentials and Coordinated Control of Groups. in: Proceedings of the 40th IEEE Conference on Decision and Control. Orlando, Florida, 2001. 2968~2973
[30] Xi Xiaorui, Abed E. H. Formation Control with Virtual Leaders and Reduced Communications. in: Proceedings of the 44th IEEE Conference on Decision and Control. Seville, Spain, 2005. 1854~1860
[31] Baras J. S, Tan Xiaobo, Hovareshti P. Decentralized Control of Autonomous Vehicles. in: Proceedings of the 42nd IEEE Conference on Decision and Control. Maui, Hawaii, 2003. 1532~1537
[32] Pereira G. A. S, Das A. K, Campos M. F. M. Formation Control with Configuration Space Constraints. in: Proceedings of the 2003 IEEE/RSJ International Conferenceon Robots and Intelligent Systems. Las Vegas, Nevada, 2003. 2755~2760
[33] Ge S. S, Fua C. H. Queues and Artificial Potential Trenches for Multirobot Formations. IEEE Transactions on Robotics, 2005, 21(4):646~656
[34] Reynolds. Flocks, herds, and schools: A Distributed Behavioral Model. Computer Graphics, 1987, 21(4):25~34
[35] Wang Long, Shi Hong, Chu Tianguang. Flocking Control of Groups of Mobile Autonomous Agents via Local Feedback. in: Proceedings of the 2005 IEEE International Conference on Control and Automation. Barcelona, Spain, 2005. 441~446
[36]徐俊明.图论及其应用.第二版.合肥:中国科学技术大学出版社, 2004. 1~43
[37] Fax J. A, Murray R. M. Information Flow and Cooperative Control of Vehicle Formations. IEEE Transactions on Automatic Control, 2004, 49(9):1465~1476
[38] Lafferriere G, Caughman J, Williams A. Graph Theoretic Methods in the Stability of Vehicle Formations. in Proceedings of the American Control Conference. Boston, Massachusetts, 2004. 3729~3734.
[39] Olfati-Saber R, Murray R. M. Distributed Cooperative Control of Multiple Vehicle Formations Using Structural Potential Functions. in: Proceedings of the 15th IFAC World Congress. Barcelona, 2002. 454~459
[40]贾秋玲,闫建国,王新民.基于势函数的多机器人系统的编队控制.机器人, 2006, 28(2):111~114
[41]杨克劭,包学游.矩阵分析.哈尔滨:哈尔滨工业大学出版社, 1995. 89~93
[42] Das S. M, Hu Y. Charlie, Lee C. S. G. Supporting Many-to-One Communication in Mobile Multi-Robot Ad Hoc Sensing Networks. in: Proceedings of the 2004 IEEE International Conference on Robotics and Automation. New Orleans, LA, 2004. 659~664
[43] Chen Z. D, Kung H. T, Vlah D. Ad Hoc Relay Wireless Networks over Moving Vehicles on Highways. in: Proceedings of ACM Symposium on MobiHoc, California, 2001. 247~250
[44] Das S. M, Hu Y. C, Lee C. S. G, et al. An Efficient Group Communication Protocolfor Mobile Robots. in: Proceedings of the 2005 IEEE International Conference on Robotics and Automation. Barcelona, 2005. 87~92