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Multi-target pursuit formation of multi-agent systems |
Yan Jing(闫敬)a),Guan Xin-Ping(关新平)a)b)†,and Luo Xiao-Yuan(罗小元)a) |
a Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China; b School of Electronic and Electric Engineering, Shanghai Jiaotong University, Shanghai 200240, China |
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Abstract The main goal of this paper is to design a team of agents that can accomplish multi-target pursuit formation using a developed leader–follower strategy. It is supposed that every target can accept a certain number of agents. First, each agent can automatically choose its target based on the distance from the agent to the target and the number of agents accepted by the target. In view of the fact that all agents are randomly dispersed in the workplace at the initial time, we present a numbering strategy for them. During the movement of agents, not every agent can always obtain pertinent state information about the targets. So, a developed leader–follower strategy and a pursuit formation algorithm are proposed. Under the proposed method, agents with the same target can maintain a circle formation. Furthermore, it turns out that the pursuit formation algorithm for agents to the desired formation is convergent. Simulation studies are provided to illustrate the effectiveness of the proposed method.
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Received: 24 June 2010
Revised: 10 August 2010
Accepted manuscript online:
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PACS:
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89.20.Ff
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(Computer science and technology)
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87.85.St
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(Robotics)
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89.65.Ef
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(Social organizations; anthropology ?)
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02.30.Em
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(Potential theory)
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Fund: Project partially supported by the National Basic Research Program of China (Grant No. 2010CB731800), the Key Project of Natural Science Foundation of China (Grant No. 60934003), the National Natural Science Foundation of China (Grant No. 61074065) and Key Project for Natural Science Research of Hebei Education Department, China (Grant No. ZD200908). |
Cite this article:
Yan Jing(闫敬), Guan Xin-Ping(关新平), and Luo Xiao-Yuan(罗小元) Multi-target pursuit formation of multi-agent systems 2011 Chin. Phys. B 20 018901
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[1] |
Yuan H L and Qu Z H 2009 IET Control Theory A 3 712 bibitem
|
[2] |
Oliveira L B and Camponogara E 2010 Transport. Res. C-Emer. 18 120 bibitem
|
[3] |
Olfati-Saber R 2006 IEEE Trans. Automat. Control. 51 401 bibitem
|
[4] |
Kolling A and Carpin S 2010 IEEE Trans. Robot. bf 26 32 bibitem
|
[5] |
Xiao F, Wang L, Chen J and Gao Y P 2009 Automatica 45 2605 bibitem
|
[6] |
Couzin I D, Krause J, Franks N R and Levin S A 2005 it Nature 433 513 bibitem
|
[7] |
Gu D B and Wang Z Y 2009 IEEE Trans. Control Syst. Tech. 17 1211 bibitem
|
[8] |
Lewis M A and Tan K H 1997 Auton. Robot. 4 387 bibitem
|
[9] |
Balch T and Arkin R C 1999 IEEE Trans. Robot. Autom. 14 1999 bibitem
|
[10] |
He Y, Zhang F M, Yang Y F and Li C F 2010 Chin. Phys. B 19 060501R bibitem
|
[11] |
Qu Z H, Wang J and Hull R A 2008 IEEE Trans. Autom. Control 53 894 bibitem
|
[12] |
Luo X Y, Li S B and Guan X P 2009 Chin. Phys. B 18 3104 bibitem
|
[13] |
Ding W, Yan G F and Lin Z Y 2010 Automatica % 46 174 bibitem
|
[14] |
Keviczky T, Borrelli F and Fregene K 2008 IEEE Trans. Intell. Transp. Syst. 16 19 bibitem
|
[15] |
Semsar-Kazerooni E and Khorasani K 2009 Automatica 45 2205 bibitem
|
[16] |
Marshall J A, Broucke M E and Francis B A 2006 % Automatica 42 3 bibitem
|
[17] |
Kim T H and Sugie T 2007 Automatica 43 1426 bibitem
|
[18] |
Marshall J A 2005 Coordinated Autonomy: Pursuit Formations of Multivehicle Systems Ph. D. Thesis (Toronto: University of Toronto of Canada) bibitem
|
[19] |
Pavone M, Smith S L, Bullo F and Frazzoli E 2009 it Proceedings of American Control Confer. St Louis, USA, June 10-12, 2009 p604 bibitem
|
[20] |
Cassandras C G, Dai L Y and Panayiotou C G 1998 IEEE Trans. Autom. Control 43 881 bibitem
|
[21] |
Choi J, Oh S and Horowitz R 2009 Automatica bf 45 2802 bibitem
|
[22] |
Luo X Y, Li S B and Guan X P 2010 Pattern Recogn. Lett. 31 800 bibitem
|
[23] |
Tan F X, Guan X P and Liu D R 2008 Chin. Phys. B 17 3531 bibitem
|
[24] |
Khatib O 1986 J. Robot. Res. 5 90 bibitem
|
[25] |
Li H, Lin P and Zhang C X 2008 Chin. Phys. B bf 17 4458 bibitem
|
[26] |
Huang L 2009 Robotic. Auton. Syst. 57 55 bibitem
|
[27] |
Huang H and Fajen B R 2006 Robot. Auton. Syst. 54 288
|
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