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Robust distributed decision-making in robot swarms: Exploiting a third truth state

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publication2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017)
Subtitle of host publicationProceedings of a meeting held 24-28 September 2017, Vancouver, British Columbia, Canada
Publisher or commissioning bodyInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages7
ISBN (Electronic)9781538626825
ISBN (Print)9781538626832
DateAccepted/In press - 30 Jun 2017
DateE-pub ahead of print - 14 Dec 2017
DatePublished (current) - Feb 2018

Publication series

ISSN (Print)2153-0866


In this paper, we investigate the best-of-n distributed decision problem in robot swarms. In this context, we compare the weighted voter model with a three-valued model that incorporates an intermediate belief state meaning either 'uncertain' or 'indifferent'. We focus particularly on the trade-off between speed of convergence to a shared belief, and robustness to the presence of unreliable individuals in the population. By means of both simulation and embodied experiments in real robot swarms of 400 Kilobots, we show that the three-valued model is much more robust than the weighted voter model, but with decreased speed of convergence.

    Research areas

  • best-of-n, decision-making, distributed, decentralised, swarm, robotics, three-valued

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