Back
pdf
Journal article

Predictive protocol of flocks with small-world connection pattern

  • Zhang, Hai-Tao The Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, China - Department of Engineering, University of Cambridge, Cambridge, UK
  • Chen, Michael Z. Q. Department of Engineering, University of Leicester, Leicester, UK - Department of Electronic Engineering, City University of Hong Kong, China
  • Zhou, Tao Department of Modern Physics, University of Science and Technology of China, Hefei, China - Department of Physics, University of Fribourg, Switzerland
    29.01.2009
Published in:
  • Physical Review E. - 2009, vol. 79, no. 01, p. 016113
pattern formation
protocols
random processes
English By introducing a predictive mechanism with small-world connections, we propose a new motion protocol for self-driven flocks. The small-world connections are implemented by randomly adding long-range interactions from the leader to a few distant agents, namely, pseudoleaders. The leader can directly affect the pseudoleaders, thereby influencing all the other agents through them efficiently. Moreover, these pseudoleaders are able to predict the leader's motion several steps ahead and use this information in decision making towards coherent flocking with more stable formation. It is shown that drastic improvement can be achieved in terms of both the consensus performance and the communication cost. From the engineering point of view, the current protocol allows for a significant improvement in the cohesion and rigidity of the formation at a fairly low cost of adding a few long-range links embedded with predictive capabilities. Significantly, this work uncovers an important feature of flocks that predictive capability and long-range links can compensate for the insufficiency of each other. These conclusions are valid for both the attractive and repulsive swarm model and the Vicsek model.
Faculty
Faculté des sciences et de médecine
Department
Département de Physique
Language
  • English
Classification
Physics
License
License undefined
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/301329
Statistics
Document views: 27 File downloads:
  • zhou_ppf.pdf: 27