Cue-based aggregation with a mobile robot swarm: a novel fuzzy-based method

Arvin F., TURGUT A. E., Bazyari F., Arikan K. B., Bellotto N., Yue S.

ADAPTIVE BEHAVIOR, vol.22, no.3, pp.189-206, 2014 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 22 Issue: 3
  • Publication Date: 2014
  • Doi Number: 10.1177/1059712314528009
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Page Numbers: pp.189-206
  • Keywords: Swarm robotics, self-organization, collective behaviour, cue-based aggregation, fuzzy logic, SELF-ORGANIZED AGGREGATION, HONEYBEE AGGREGATION, DECISION-MAKING, BEHAVIOR, EMBODIMENT
  • Middle East Technical University Affiliated: No


Aggregation in swarm robotics is referred to as the gathering of spatially distributed robots into a single aggregate. Aggregation can be classified as cue-based or self-organized. In cue-based aggregation, there is a cue in the environment that points to the aggregation area, whereas in self-organized aggregation no cue is present. In this paper, we proposed a novel fuzzy-based method for cue-based aggregation based on the state-of-the-art BEECLUST algorithm. In particular, we proposed three different methods: naive, that uses a deterministic decision-making mechanism; vector-averaging, using a vectorial summation of all perceived inputs; and fuzzy, that uses a fuzzy logic controller. We used different experiment settings: one-source and two-source environments with static and dynamic conditions to compare all the methods. We observed that the fuzzy method outperformed all the other methods and it is the most robust method against noise.