Professor Farshad Arvin farshad.arvin@durham.ac.uk
Professor
Professor Farshad Arvin farshad.arvin@durham.ac.uk
Professor
Ali Emre Turgut
Farhad Bazyari
Kutluk Bilge Arikan
Nicola Bellotto
Shigang Yue
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: naïve, 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.
Arvin, F., Turgut, A. E., Bazyari, F., Arikan, K. B., Bellotto, N., & Yue, S. (2014). Cue-based aggregation with a mobile robot swarm: a novel fuzzy-based method. Adaptive Behavior, 22(3), 189-206. https://doi.org/10.1177/1059712314528009
Journal Article Type | Article |
---|---|
Online Publication Date | May 1, 2014 |
Publication Date | 2014-06 |
Deposit Date | May 27, 2022 |
Journal | Adaptive Behavior |
Print ISSN | 1059-7123 |
Electronic ISSN | 1741-2633 |
Publisher | SAGE Publications |
Volume | 22 |
Issue | 3 |
Pages | 189-206 |
DOI | https://doi.org/10.1177/1059712314528009 |
Public URL | https://durham-repository.worktribe.com/output/1205305 |
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