Flocking behavior with multiple leaders and global trajectory

被引:5
作者
Li Meng [1 ]
Liang Jia-hong [1 ]
Li Shi-lei [2 ]
机构
[1] Natl Univ Def Technol, Coll Informat Syst & Management, Changsha 410073, Hunan, Peoples R China
[2] Naval Univ Engn, Coll Elect Engn, Dept Informat Secur, Wuhan 430033, Peoples R China
基金
中国国家自然科学基金;
关键词
multi-agent system; group of agents; flocking behavior; distributed control; global trajectory; MULTIAGENT SYSTEMS; ADAPTIVE FLOCKING;
D O I
10.1007/s11771-014-2184-0
中图分类号
TF [冶金工业];
学科分类号
0806 ;
摘要
Aiming at the group of autonomous agents consisting of multiple leader agents and multiple follower ones, a flocking behavior method with multiple leaders and a global trajectory was proposed. In this flocking method, the group leaders can attain the information of the global trajectory, while each follower can communicate with its neighbors and corresponding leader but does not have global knowledge. Being to a distributed control method, the proposed method firstly sets a movable imaginary point on the global trajectory to ensure that the center and average velocity of the leader agents satisfy the constraints of the global trajectory. Secondly, a two-stage strategy was proposed to make the whole group satisfy the constraints of the global trajectory. Moreover, the distance between the center of the group and the desired trajectory was analyzed in detail according to the number ratio of the followers to the leaders. In this way, on one hand, the agents of the group emerge a basic flocking behavior; on the other hand, the center of the group satisfies the constraints of global trajectory. Simulation results demonstrate the effectiveness of the proposed method.
引用
收藏
页码:2324 / 2333
页数:10
相关论文
共 18 条
[1]   Adaptive flocking control of nonlinear multi-agent systems with directed switching topologies and saturation constraints [J].
Atrianfar, Hajar ;
Haeri, Mohammad .
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2013, 350 (06) :1545-1561
[2]   Interactive robot trajectory planning and simulation using Augmented Reality [J].
Fang, H. C. ;
Ong, S. K. ;
Nee, A. Y. C. .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2012, 28 (02) :227-237
[3]   Unifying microscopic flocking motion models for virtual, robotic, and biological flock members [J].
Fine, Benjamin T. ;
Shell, Dylan A. .
AUTONOMOUS ROBOTS, 2013, 35 (2-3) :195-219
[4]   Leader-Follower Flocking: Algorithms and Experiments [J].
Gu, Dongbing ;
Wang, Zongyao .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2009, 17 (05) :1211-1219
[5]   Using Fuzzy Logic to Design Separation Function in Flocking Algorithms [J].
Gu, Dongbing ;
Flu, Huosheng .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2008, 16 (04) :826-838
[6]   Flocking techniques to naturally support navigation in large and open virtual worlds [J].
Ibanez, Jesus ;
Delgado-Mata, Carlos .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2012, 25 (01) :119-129
[7]   Flocking for multi-agent dynamic systems: Algorithms and theory [J].
Olfati-Saber, R .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2006, 51 (03) :401-420
[8]  
Su H., 2007, 46th IEEE Conference on Decision and Control, P1429
[9]  
Su HS, 2007, IEEE DECIS CONTR P, P374
[10]  
Su HS, 2008, ASIAN J CONTROL, V10, P238, DOI [10.1002/asjc.22, 10.1002/asjc.022]