Robust morphogenesis of robotic swarms

Hiroki Sayama*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)


A novel framework for designing and implementing morphogenetic robotic swarms by using very simple, particle-like mobile robots is presented. This simple model extension naturally enables growth and self-assembly of robotic swarms by local information transmission and stochastic differentiation, and moreover, self-repair by stochastic re-differentiation of robots. Swarm Chemistry has been used as the basic model for the proposed design framework. For a given swarm, specifications for its macroscopic properties are indirectly and implicitly woven into a list of different kinetic parameter settings for each swarm component. Once a robot is activated, it simply reacts kinetically to nearby robots and independently re-differentiates with small probability. This architecture demonstrates dynamic production and maintenance of patterns, which allows robust, adaptive behaviors under variable environmental conditions, including self-repair with no central controller. If the number of robots is increased too much, the swarm loses coherence and the design embedded in the original recipe is not reproduced correctly.

Original languageEnglish
Article number5508726
Pages (from-to)43-49
Number of pages7
JournalIEEE Computational Intelligence Magazine
Issue number3
Publication statusPublished - 2010 Aug
Externally publishedYes

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Artificial Intelligence


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