群体机器人集结控制研究
|
摘要
群体机器人是当前理论与实际应用中的一个研究热点,其运行环境复杂多变,机器人之间的通信、协同、控制中存在一些有待解决的问题。本文研究群体机器人的集结问题,提出一些新的方法来解决这一问题,本文的主要工作如下：
(1)线性情形下的群体机器人集结控制问题。考虑没有虚拟领导者的情形,根据机器人间的相互位置信息构建的势场函数和相对速度信息的一致性方法,实现群体机器人的集结行为。考虑带有虚拟领导者的情形,针对所有机器人都可以接收到虚拟领导者和仅有一个机器人可以接收到虚拟领导者状态信息两种情形,分别提出了具有网络连通性保持的分布式控制方法,解决群体行为的集结控制。在此基础上,研究时变虚拟领导者对群体行为以及机器人之间作用权值动态变化对群体行为的影响。
(2)仅考虑位置信息情形的群体机器人集结控制研究。机器人的速度信息一般难以准确获取,仅考虑位置信息情形的群体机器人动态行为渐近控制是个很有价值的问题。考虑没有虚拟领导者的情形,根据机器人之间的相互位置信息构建势场函数并且通过位置信息实现对速度信息的观测,提出了网络连通性保持的分布式控制算法。考虑带有虚拟领导者情形,研究群体行为的动态演化,提出一新的分布式控制算法实现机器人的速度信息最终与虚拟领导者的信息保持一致,并且所有机器人的最终会聚集到一起。
(3)非线性情形下的群体机器人集结控制研究。针对复杂群体行为下,研究机器人之间的非线性耦合关系,研究时不变与时变虚拟领导者情形的群体行为集结控制。并且深入研究机器人之间相互作用权值动态变化情形,拓宽了群体行为的应用领域。根据机器人之间的非线性耦合,相互势场函数以及虚拟领导者作用,提出了网络连通性保持的分布式群体机器人集结控制算法实现群体行为最终形成集结。
研究群体机器人集结问题,针对不同情形,分别提出相应的分布式控制算法,理论分析证明了所有机器人的速度状态信息会收敛到一致,并且所有机器人的最终也可以形成集结。最后通过数值仿真实验验证了所提出分布式群集算法有效性。
Rendezvous of flocking robots is one of hottest points in theory research and engineering application currently. There are many problems to be solved in communication, cooperation and control strategies for swarm robots system. Some new methods are proposed to solve rendezvous control problems of swarm robots in this thesis, and main work is arranged as the following:
(1) Rendezvous control problems of swarm robots in the case of linear coupling relationship. Firstly, a distributed control algorithm is proposed to solve rendezvous problem of swarm robots without a virtual leader according to relative position and velocity information. Secondly, a distributed control algorithm is proposed with a virtual leader while the connectivity of the network topology preserved. Based on linear coupled relationship of swarm robots, some other factors are considered, such as a time variant leader and dynamical adaptive parameteters.
(2) Rendezvous control problems of swarm robots with only position information. Generally speaking, it's difficult to get velocity information of robots. One distributed predictor is also built based on relative position. Distributed control algorithms are proposed to solve rendezvous control proble. Swarm robots system with one virtual leader is researched in this case, and distributed control algorithms are proposed while connectivity of robots network preserved. All the robots will reach the same place with the same velocity value.
(3) Nonlinear rendezvous control problem of swarm robots is also deeply researched in the thesis. For complex flocking behavior, nonlinear coupling relationship between robots is considered. Considering swarm system without and with a virtual leader, according to effects of nonlinear coupling relationship between robots, relative potential function and a virtual leader, distributed control algorithm with nonlinear coupling function is proposed while connectivity of robots network preserved. In the case of dynamical parameters adaptive control in swarm robots, distributed control algorithm is proposed to solve this problem.
Research on rendezvous problem of swarm robots, for different cases, some distributed control algorithms are proposed to solve different problems. Theory analysis proves that the algorithms can keep robot network connected, and all the robots will reach the same place with the same velocity value. Finally, effectiveness of the proposed distributed rendezvous control algorithms is validated through simulation experiments. For complicated behavior of swarm robots, the proposed control algorithms can be used to different application case. It can be used in practicial engineering application. The proposed algorithm will give a guideline to design and solve swarm emergence problem.
(1)线性情形下的群体机器人集结控制问题。考虑没有虚拟领导者的情形,根据机器人间的相互位置信息构建的势场函数和相对速度信息的一致性方法,实现群体机器人的集结行为。考虑带有虚拟领导者的情形,针对所有机器人都可以接收到虚拟领导者和仅有一个机器人可以接收到虚拟领导者状态信息两种情形,分别提出了具有网络连通性保持的分布式控制方法,解决群体行为的集结控制。在此基础上,研究时变虚拟领导者对群体行为以及机器人之间作用权值动态变化对群体行为的影响。
(2)仅考虑位置信息情形的群体机器人集结控制研究。机器人的速度信息一般难以准确获取,仅考虑位置信息情形的群体机器人动态行为渐近控制是个很有价值的问题。考虑没有虚拟领导者的情形,根据机器人之间的相互位置信息构建势场函数并且通过位置信息实现对速度信息的观测,提出了网络连通性保持的分布式控制算法。考虑带有虚拟领导者情形,研究群体行为的动态演化,提出一新的分布式控制算法实现机器人的速度信息最终与虚拟领导者的信息保持一致,并且所有机器人的最终会聚集到一起。
(3)非线性情形下的群体机器人集结控制研究。针对复杂群体行为下,研究机器人之间的非线性耦合关系,研究时不变与时变虚拟领导者情形的群体行为集结控制。并且深入研究机器人之间相互作用权值动态变化情形,拓宽了群体行为的应用领域。根据机器人之间的非线性耦合,相互势场函数以及虚拟领导者作用,提出了网络连通性保持的分布式群体机器人集结控制算法实现群体行为最终形成集结。
研究群体机器人集结问题,针对不同情形,分别提出相应的分布式控制算法,理论分析证明了所有机器人的速度状态信息会收敛到一致,并且所有机器人的最终也可以形成集结。最后通过数值仿真实验验证了所提出分布式群集算法有效性。
Rendezvous of flocking robots is one of hottest points in theory research and engineering application currently. There are many problems to be solved in communication, cooperation and control strategies for swarm robots system. Some new methods are proposed to solve rendezvous control problems of swarm robots in this thesis, and main work is arranged as the following:
(1) Rendezvous control problems of swarm robots in the case of linear coupling relationship. Firstly, a distributed control algorithm is proposed to solve rendezvous problem of swarm robots without a virtual leader according to relative position and velocity information. Secondly, a distributed control algorithm is proposed with a virtual leader while the connectivity of the network topology preserved. Based on linear coupled relationship of swarm robots, some other factors are considered, such as a time variant leader and dynamical adaptive parameteters.
(2) Rendezvous control problems of swarm robots with only position information. Generally speaking, it's difficult to get velocity information of robots. One distributed predictor is also built based on relative position. Distributed control algorithms are proposed to solve rendezvous control proble. Swarm robots system with one virtual leader is researched in this case, and distributed control algorithms are proposed while connectivity of robots network preserved. All the robots will reach the same place with the same velocity value.
(3) Nonlinear rendezvous control problem of swarm robots is also deeply researched in the thesis. For complex flocking behavior, nonlinear coupling relationship between robots is considered. Considering swarm system without and with a virtual leader, according to effects of nonlinear coupling relationship between robots, relative potential function and a virtual leader, distributed control algorithm with nonlinear coupling function is proposed while connectivity of robots network preserved. In the case of dynamical parameters adaptive control in swarm robots, distributed control algorithm is proposed to solve this problem.
Research on rendezvous problem of swarm robots, for different cases, some distributed control algorithms are proposed to solve different problems. Theory analysis proves that the algorithms can keep robot network connected, and all the robots will reach the same place with the same velocity value. Finally, effectiveness of the proposed distributed rendezvous control algorithms is validated through simulation experiments. For complicated behavior of swarm robots, the proposed control algorithms can be used to different application case. It can be used in practicial engineering application. The proposed algorithm will give a guideline to design and solve swarm emergence problem.
引文
[1]李文锋.无线传感器网络与移动机器人控制.北京：科学出版社,2009.
[2]谭民,王硕,曹志强.多机器人系统.北京：清华大学出版社,2005.
[3]王越超.多机器人协作系统研究.哈尔滨工业大学博士论文[D],1999.
[4]Dorigo M, Sahin E. Special Issue: Swarm Robotics[J]. Autonomous Robots,2004,17: pp111-113.
[5]Swarm-bots:Swarms of self-assembling artifacts, http://www.swarm-bots.org/.
[6]Communication Policies in Swarm Intelligent Systems, http://code.ulb.ac.be/iridia.a ctivities.projects.php?id=21.
[7]J. S, W. Heinz. The I-SWARM project:intelligent small world autonomous robots for micro-manipulation [C]. LNCS 3342:Swarm Robotics, Beilin:Springer,2005:pp70-83.
[8]David P, D. Mike. Pheromone Robotics [J]. Autonomous Robots,2001,11:pp319-324.
[9]Swarmanoid:Towards Humanoid Robotic Swarms, http://www.swarmanoid.org/pu blications_byrype.php.
[10]GroundScouts Project, http://www.swarm-robotics.org/index.php/Main_Page.
[11]SWARMS projects, http://www.grasp.upenn.edu/research/swarms.
[12]D.Zhang, Y. Fang, G. Xie, J. Yu and L. Wang. Coordinating Dual-mode Biomimetic Robotic Fish in Box-pushing Task, Lecture Notes in Artificial Intelligence. Springer-Verlag, Berlin Heidelberg,2005, vol.3630, pp.815-824.
[13]D. Zhang, L. Wang, G. Xie, and W. Zhang. Coordinated Collision Avoidance of Multiple Biomimetic Robotic Fish, Lecture Notes in Artificial Intelligence. Springer-Verlag, Berlin Heidelberg,2005, pp.215-224.
[14]D. Zhang, G. Xie, J. Yu, and L. Wang. An Adaptive Task Assignment Method for Multiple Mobile Robots via Swarm Intelligence Approach, The 6th IEEE International Symposium on Computational Intelligence in Robotics and Automation, July 2005, pp. 415-420.
[15]A. Jadbabaie, J. Lin, and A. S. Morse. Coordination of groups of mobile autonomous agents using nearest neighbor rules, IEEE Transactions on Automatic Control, July 2002, 48:pp988-1001.
[16]R. Olfati-Saber and R. M. Murray., Consensus problems in networks of agents with switching topology and time-delays, IEEE Trans. on Automatic Control,2004,49: pp1520-1533.
[17]W. Ren, Randal W.Beard, and Timothy W. McLain. Coordination variables and consensus building in multiple vehicle systems. Lecture Notes in Control and Information Sciences, vol.390, pp.171-188, Springer-Verlag, Berlin,2005.
[18]W. Ren, Randal W.Beard. Distributed Consensus in Mutli-vehicle Cooperative Control, Communications and Control Engineering Series, Springer-Verlag, London,2008
[19]W. Ren. On consensus algorithms for double-integrator dynamics, Proceedings of the IEEE Conference on Decision and Control, New Orleans, LA,2007.
[20]W. Ren, Multi-vehicle consensus with a time-varying reference state, Systems and Control Letters, vol.56, no.7-8, pp.474-483, July 2007.
[21]雷斌,群体机器人系统合作控制问题研究,武汉理工大学博十学位论文[D],2009年12月.
[22]R. Olfati-Saber. Ultra fast consensus in small-world networks. Proc. of the 2005 American Control Conference,2005:pp2371-2378.
[23]R. Olfati-Saber. Distributed Kalman Filter with Embedded Consensus Filters, Proc. of the joint CDC-ECC'05 Conference,2005.
[24]R. Olfati-Saber, E.Franco, E. Frazzoli, J.S. Shamma, Belief consensus and distributed hypothesis testing in sensor networks, Workshop on Networked Embedded Sensing and Control,2005.
[25]J. Lin and A. S. Morse, The Multi-Agent Rendezvous Problem-The Asynchronous Case, Proceeding of the 43rd IEEE Conference on Decision and Control,2004.
[26]A. Fax and R. M. Murray. Information flow and cooperative control of vehicle formations. IEEE Transactions on Automatic Control, September 2004,49:pp1465-1475.
[27]R. Olfati-Saber. Flocking with Obstacle Avoidance. Technical Report 2003-006, California Institute of Technology, Control and Dynamical Systems, Pasadena, California, February 2003.
[28]Martin Schmalz Masayuki Fujita Oliver Sawodny, Directed Gossip Algorithms, Consensus Problems, and Stability Effects of Noise Trading. European Journal of Economic and Social Systems, vol.43, pp1-8,2009
[29]S. H. Strogatz. From Kuramoto to Crawford:Exploring the onset of synchronization in populations of coupled oscillators, Physica D, vol.143, pp.1-20,2000.
[30]R. Olfati-Saber and R. M. Murray, Distributed cooperative control of multiple vehicle formations using structural potential functions, presented at the 15th IFAC World Congr., Barcelona, Spain, Jul.2002.
[31]C.Reynolds, Flocks, birds, and schools:a distributed behavioral model, Computer Graphics,1987,21:pp25-34.
[32]T. Vicsek, A. Cziro'ok, E.Ben-Jacob, and O.Cohen, I. Shochet. Novel type of phase transition in a system of self-deriven particles. Physical Review Letters, August 1995, 75(6):pp1226-1229.
[33]R. Olfati-Saber and R. M. Murray. Distributed cooperative control of multiple vehicle formations using structural potential functions. The 15th IFAC World Congress, June 2002.
[34]W. Ren. On consensus algorithms for double-integrator dynamics. IEEE Transactions on Automatic Control,2008,53(6):pp1503-1509.
[35]Lin, J. and Morse, AS and Anderson, BDO, The multi-agent rendezvous problem. Part 1:The synchronous case, SIAM Journal on Control and Optimization,2007,46(6), pp2096-2119.
[36]Lin, J. and Morse, AS and Anderson, BDO, The multi-agent rendezvous problem. Part 2:The asynchronous case, SIAM Journal on Control and Optimization,2007,46(6), pp2120-2147.
[37]H. Tanner, A Jadbabaie and G. Pappas. Flocking in Fixed and Switching Networks, IEEE Transactions on Automatic Control, Vol.52, April 2005, pp863-868
[38]R. Olfati-Saber, Flocking for Multi-Agent Dynamic Systems:Algorithms and Theory, IEEE Transactions on Automatic Control,2005.
[39]H. Su, X. Wang, and Z. Lin, Flocking of multi-agents with a virtual leader, IEEE Transactions on Automatic Control, vol.54, no.2, pp.293-307,2009.
[40]R. Olfati-Saber. Flocking with Obstacle Avoidance. Technical Report 2003-006, California Institute of Technology, Control and Dynamical Systems, Pasadena, California, February 2003.
[41]Jing Han, Ming Li, Lei Guo. Soft control on collective behavior of a group of autonomous agents by a shill agent [J]. J of Systems Science and Complexity,2006, 19(1), pp54-62.
[42]潘福臣,陈雪波,李琳.群集模型的软控制研究[J].科学技术与工程,2009(17)：pp4905-4909.
[43]Michael M. Zavlanos, Ali Jadbabaie and George J. Pappas, Flocking while Preserving Network Connectivity, Proceedings of the 46th IEEE Conference on Decision and Control New Orleans, LA, USA, Dec. pp 12-14,2007
[44]H. Su, X. Wang and G. Chen, A connectivity-preserving flocking algorithm for multi-agent systems based only on position measurements, International Journal of Control,2009,82(7):pp1334-1343.
[2]谭民,王硕,曹志强.多机器人系统.北京：清华大学出版社,2005.
[3]王越超.多机器人协作系统研究.哈尔滨工业大学博士论文[D],1999.
[4]Dorigo M, Sahin E. Special Issue: Swarm Robotics[J]. Autonomous Robots,2004,17: pp111-113.
[5]Swarm-bots:Swarms of self-assembling artifacts, http://www.swarm-bots.org/.
[6]Communication Policies in Swarm Intelligent Systems, http://code.ulb.ac.be/iridia.a ctivities.projects.php?id=21.
[7]J. S, W. Heinz. The I-SWARM project:intelligent small world autonomous robots for micro-manipulation [C]. LNCS 3342:Swarm Robotics, Beilin:Springer,2005:pp70-83.
[8]David P, D. Mike. Pheromone Robotics [J]. Autonomous Robots,2001,11:pp319-324.
[9]Swarmanoid:Towards Humanoid Robotic Swarms, http://www.swarmanoid.org/pu blications_byrype.php.
[10]GroundScouts Project, http://www.swarm-robotics.org/index.php/Main_Page.
[11]SWARMS projects, http://www.grasp.upenn.edu/research/swarms.
[12]D.Zhang, Y. Fang, G. Xie, J. Yu and L. Wang. Coordinating Dual-mode Biomimetic Robotic Fish in Box-pushing Task, Lecture Notes in Artificial Intelligence. Springer-Verlag, Berlin Heidelberg,2005, vol.3630, pp.815-824.
[13]D. Zhang, L. Wang, G. Xie, and W. Zhang. Coordinated Collision Avoidance of Multiple Biomimetic Robotic Fish, Lecture Notes in Artificial Intelligence. Springer-Verlag, Berlin Heidelberg,2005, pp.215-224.
[14]D. Zhang, G. Xie, J. Yu, and L. Wang. An Adaptive Task Assignment Method for Multiple Mobile Robots via Swarm Intelligence Approach, The 6th IEEE International Symposium on Computational Intelligence in Robotics and Automation, July 2005, pp. 415-420.
[15]A. Jadbabaie, J. Lin, and A. S. Morse. Coordination of groups of mobile autonomous agents using nearest neighbor rules, IEEE Transactions on Automatic Control, July 2002, 48:pp988-1001.
[16]R. Olfati-Saber and R. M. Murray., Consensus problems in networks of agents with switching topology and time-delays, IEEE Trans. on Automatic Control,2004,49: pp1520-1533.
[17]W. Ren, Randal W.Beard, and Timothy W. McLain. Coordination variables and consensus building in multiple vehicle systems. Lecture Notes in Control and Information Sciences, vol.390, pp.171-188, Springer-Verlag, Berlin,2005.
[18]W. Ren, Randal W.Beard. Distributed Consensus in Mutli-vehicle Cooperative Control, Communications and Control Engineering Series, Springer-Verlag, London,2008
[19]W. Ren. On consensus algorithms for double-integrator dynamics, Proceedings of the IEEE Conference on Decision and Control, New Orleans, LA,2007.
[20]W. Ren, Multi-vehicle consensus with a time-varying reference state, Systems and Control Letters, vol.56, no.7-8, pp.474-483, July 2007.
[21]雷斌,群体机器人系统合作控制问题研究,武汉理工大学博十学位论文[D],2009年12月.
[22]R. Olfati-Saber. Ultra fast consensus in small-world networks. Proc. of the 2005 American Control Conference,2005:pp2371-2378.
[23]R. Olfati-Saber. Distributed Kalman Filter with Embedded Consensus Filters, Proc. of the joint CDC-ECC'05 Conference,2005.
[24]R. Olfati-Saber, E.Franco, E. Frazzoli, J.S. Shamma, Belief consensus and distributed hypothesis testing in sensor networks, Workshop on Networked Embedded Sensing and Control,2005.
[25]J. Lin and A. S. Morse, The Multi-Agent Rendezvous Problem-The Asynchronous Case, Proceeding of the 43rd IEEE Conference on Decision and Control,2004.
[26]A. Fax and R. M. Murray. Information flow and cooperative control of vehicle formations. IEEE Transactions on Automatic Control, September 2004,49:pp1465-1475.
[27]R. Olfati-Saber. Flocking with Obstacle Avoidance. Technical Report 2003-006, California Institute of Technology, Control and Dynamical Systems, Pasadena, California, February 2003.
[28]Martin Schmalz Masayuki Fujita Oliver Sawodny, Directed Gossip Algorithms, Consensus Problems, and Stability Effects of Noise Trading. European Journal of Economic and Social Systems, vol.43, pp1-8,2009
[29]S. H. Strogatz. From Kuramoto to Crawford:Exploring the onset of synchronization in populations of coupled oscillators, Physica D, vol.143, pp.1-20,2000.
[30]R. Olfati-Saber and R. M. Murray, Distributed cooperative control of multiple vehicle formations using structural potential functions, presented at the 15th IFAC World Congr., Barcelona, Spain, Jul.2002.
[31]C.Reynolds, Flocks, birds, and schools:a distributed behavioral model, Computer Graphics,1987,21:pp25-34.
[32]T. Vicsek, A. Cziro'ok, E.Ben-Jacob, and O.Cohen, I. Shochet. Novel type of phase transition in a system of self-deriven particles. Physical Review Letters, August 1995, 75(6):pp1226-1229.
[33]R. Olfati-Saber and R. M. Murray. Distributed cooperative control of multiple vehicle formations using structural potential functions. The 15th IFAC World Congress, June 2002.
[34]W. Ren. On consensus algorithms for double-integrator dynamics. IEEE Transactions on Automatic Control,2008,53(6):pp1503-1509.
[35]Lin, J. and Morse, AS and Anderson, BDO, The multi-agent rendezvous problem. Part 1:The synchronous case, SIAM Journal on Control and Optimization,2007,46(6), pp2096-2119.
[36]Lin, J. and Morse, AS and Anderson, BDO, The multi-agent rendezvous problem. Part 2:The asynchronous case, SIAM Journal on Control and Optimization,2007,46(6), pp2120-2147.
[37]H. Tanner, A Jadbabaie and G. Pappas. Flocking in Fixed and Switching Networks, IEEE Transactions on Automatic Control, Vol.52, April 2005, pp863-868
[38]R. Olfati-Saber, Flocking for Multi-Agent Dynamic Systems:Algorithms and Theory, IEEE Transactions on Automatic Control,2005.
[39]H. Su, X. Wang, and Z. Lin, Flocking of multi-agents with a virtual leader, IEEE Transactions on Automatic Control, vol.54, no.2, pp.293-307,2009.
[40]R. Olfati-Saber. Flocking with Obstacle Avoidance. Technical Report 2003-006, California Institute of Technology, Control and Dynamical Systems, Pasadena, California, February 2003.
[41]Jing Han, Ming Li, Lei Guo. Soft control on collective behavior of a group of autonomous agents by a shill agent [J]. J of Systems Science and Complexity,2006, 19(1), pp54-62.
[42]潘福臣,陈雪波,李琳.群集模型的软控制研究[J].科学技术与工程,2009(17)：pp4905-4909.
[43]Michael M. Zavlanos, Ali Jadbabaie and George J. Pappas, Flocking while Preserving Network Connectivity, Proceedings of the 46th IEEE Conference on Decision and Control New Orleans, LA, USA, Dec. pp 12-14,2007
[44]H. Su, X. Wang and G. Chen, A connectivity-preserving flocking algorithm for multi-agent systems based only on position measurements, International Journal of Control,2009,82(7):pp1334-1343.