Patterns, transitions and the role of leaders in the collective dynamics of a simple robotic flock

Norbert Tarcai, Csaba Virágh, Dániel Ábel, Máté Nagy, Péter L. Várkonyi, Gábor Vásárhelyi, Tamás Vicsek

Research output: Contribution to journalArticle

19 Citations (Scopus)


We have developed an experimental setup of very simple self-propelled robots to observe collective motion emerging as a result of inelastic collisions only. A circular pool and commercial RC boats were the basis of our first setup, where we demonstrated that jamming, clustering, disordered and ordered motion are all present in such a simple experiment and showed that the noise level has a fundamental role in the generation of collective dynamics. Critical noise ranges and the transition characteristics between the different collective patterns were also examined. In our second experiment we used a real-time tracking system and a few steerable model boats to introduce intelligent leaders into the flock. We demonstrated that even a very small portion of guiding members can determine group direction and enhance ordering through inelastic collisions. We also showed that noise can facilitate and speed up ordering with leaders. Our work was extended with an agent-based simulation model, too, and close similarity between real and simulation results was observed. The simulation results show clear statistical evidence of three states and negative correlation between density and ordered motion due to the onset of jamming. Our experiments confirm the different theoretical studies and simulation results in the literature on the subject of collision-based, noise-dependent and leader-driven self-propelled particle systems.

Original languageEnglish
Article numberP04010
JournalJournal of Statistical Mechanics: Theory and Experiment
Issue number4
Publication statusPublished - Apr 1 2011


  • Phase transitions into absorbing states (experiment)
  • self-organized criticality (experiment)
  • stationary states
  • stochastic particle dynamics (theory)

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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