Collective dynamic behavior of anisotropic foraging swarms

被引:0
|
作者
Shi, Hong [1 ]
Wang, Long [1 ]
Chu, Tianguang [1 ]
Xu, Minjie [2 ]
机构
[1] Peking Univ, Coll Engn, Ctr Syst & Control, Dept Ind Engn & Management, Beijing 100871, Peoples R China
[2] Beijing Jiatong Univ, Sch Elect Engn, Beijing 100044, Peoples R China
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper considers an anisotropic swarm model with an attraction/repulsion function under external profiles. We study its aggregation properties and show that the swarm members will aggregate and eventually form a cohesive cluster of finite size around their weighted center in a finite time. In the model, the motion of each agent is a combination of the interindividual interactions and the interaction of the agent with external environment. Numerical simulations demonstrate that all agents will eventually enter and remain in a bounded region around the weighted center. The swarm may exhibit complex oscillatory or spiral motion due to the asymmetry of the coupling structure and the effect of the external profile. The model in this paper is more general than isotropic swarms and our results provide further insight into the effect of the interaction pattern and the external profile on individual motion in a swarm system.
引用
收藏
页码:2204 / +
页数:2
相关论文
共 50 条
  • [31] Collective Change Detection: Adaptivity to Dynamic Swarm Densities and Light Conditions in Robot Swarms
    Wahby, Mostafa
    Petzold, Julian
    Eschke, Catriona
    Schmickl, Thomas
    Hamann, Heiko
    ALIFE 2019: THE 2019 CONFERENCE ON ARTIFICIAL LIFE, 2019, : 642 - 649
  • [32] Distributed Sequential Task Allocation in Foraging Swarms
    Goldingay, Harry
    van Mourik, Jort
    2013 IEEE 7TH INTERNATIONAL CONFERENCE ON SELF-ADAPTIVE AND SELF-ORGANIZING SYSTEMS (SASO), 2013, : 149 - 158
  • [33] Stable social foraging swarms in a noisy environment
    Liu, TF
    Passino, KM
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2004, 49 (01) : 30 - 44
  • [34] A hierarchical training method of generating collective foraging behavior for a robotic swarm
    Jin, Boyin
    Liang, Yupeng
    Han, Ziyao
    Hiraga, Motoaki
    Ohkura, Kazuhiro
    ARTIFICIAL LIFE AND ROBOTICS, 2022, 27 (01) : 137 - 141
  • [35] A hierarchical training method of generating collective foraging behavior for a robotic swarm
    Boyin Jin
    Yupeng Liang
    Ziyao Han
    Motoaki Hiraga
    Kazuhiro Ohkura
    Artificial Life and Robotics, 2022, 27 : 137 - 141
  • [36] A Multiscale Review of Behavioral Variation in Collective Foraging Behavior in Honey Bees
    Lemanski, Natalie J.
    Cook, Chelsea N.
    Smith, Brian H.
    Pinter-Wollman, Noa
    INSECTS, 2019, 10 (11)
  • [37] Dynamic anisotropic behavior of amorphous polymers
    Chen, W
    Lu, F
    PROCEEDINGS OF THE SEM IX INTERNATIONAL CONGRESS ON EXPERIMENTAL MECHANICS, 2000, : 620 - 623
  • [38] Foraging motion of swarms with leaders as Nash equilibria
    Yildiz, Aykut
    Ozguler, A. Bulent
    AUTOMATICA, 2016, 73 : 163 - 168
  • [39] Tracking Pedestrians with Bacterial Foraging Optimization Swarms
    Hoang Thanh Nguyen
    Bhanu, Bir
    2011 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2011, : 491 - 495
  • [40] Controlling two-dimensional collective formation and cooperative behavior of magnetic microrobot swarms
    Dong, Xiaoguang
    Sitti, Metin
    INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH, 2020, 39 (05): : 617 - 638