The k-unanimity rule for self-organized decision-making in swarms of robots

Alexander Scheidler, Arne Brutschy, Eliseo Ferrante, Marco Dorigo

Research output: Contribution to JournalArticleAcademicpeer-review


In this paper, we propose a collective decision-making method for swarms of robots. The method enables a robot swarm to select, from a set of possible actions, the one that has the fastest mean execution time. By means of positive feedback the method achieves consensus on the fastest action. The novelty of our method is that it allows robots to collectively find consensus on the fastest action without measuring explicitly the execution times of all available actions. We study two analytical models of the decision-making method in order to understand the dynamics of the consensus formation process. Moreover, we verify the applicability of the method in a real swarm robotics scenario. To this end, we conduct three sets of experiments that show that a robotic swarm can collectively select the shortest of two paths. Finally, we use a Monte Carlo simulation model to study and predict the influence of different parameters on the method.

Original languageEnglish
Article number7113800
Pages (from-to)1175-1188
Number of pages14
JournalIEEE Transactions on Cybernetics
Issue number5
Publication statusPublished - 1 May 2016
Externally publishedYes


  • Intelligent robots
  • intelligent systems
  • multi-robot systems


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