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Impact of the Update Time on the Aggregation of Robotic Swarms Through Informed Robots

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From Animals to Animats 16 (SAB 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13499))

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Abstract

Self-organised aggregation is one of the basic collective behaviours studied in swarm robotics. In this paper, we investigate an aggregation problem occurring on two different sites. Previous studies have shown that a minority of robots, informed about the site on which they have to aggregate, can control the final distribution of the entire robot swarm on the sites. We reproduce this strategy by adapting the previous probabilistic finite-state machine to a new simulated robotic platform: the Kilobot. Our simulation results highlight that the update time (i.e., the amount of time a robot waits before making a decision on leaving a site) impacts the dynamics of the aggregation process. Namely, a longer update time lowers the number of robots wandering in the arena, but can slow down the dynamics when the target final distribution is far from the one initially formed. To ensure a low number of wandering robots while maintaining a quick convergence towards the target final distribution of the swarm, we introduce the concept of a dynamic update time increasing during the aggregation process.

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Acknowledgements

This work was supported by Service Public de Wallonie Recherche under grant n\(^{\circ }\) 2010235 - ARIAC by DIGITALWALLONIA4.AI; by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 681872); and by Belgium’s Wallonia-Brussels Federation through the ARC Advanced Project GbO (Guaranteed by Optimization). AR and MB acknowledge the financial support from the Belgian F.R.S.-FNRS, of which they are Chargé de Recherches and Directeur de Recherches, respectively.

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Authors and Affiliations

  1. Faculty of Computer Science, University of Namur, Namur, Belgium

    Antoine Sion & Elio Tuci

  2. IRIDIA, Université Libre de Bruxelles, Brussels, Belgium

    Andreagiovanni Reina & Mauro Birattari

Authors
  1. Antoine Sion
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  2. Andreagiovanni Reina
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  3. Mauro Birattari
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  4. Elio Tuci
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Corresponding author

Correspondence to Antoine Sion .

Editor information

Editors and Affiliations

  1. ETIS, CY Cergy Paris Université, Cergy-Pontoise, France

    Lola Cañamero

  2. ETIS, CY Cergy Paris Université, Cergy-Pontoise, France

    Philippe Gaussier

  3. Aberystwyth University, Aberystwyth, UK

    Myra Wilson

  4. ETIS, CY Cergy Paris Université, Cergy-Pontoise, France

    Sofiane Boucenna

  5. ETIS, CY Cergy Paris Université, Cergy-Pontoise, France

    Nicolas Cuperlier

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Sion, A., Reina, A., Birattari, M., Tuci, E. (2022). Impact of the Update Time on the Aggregation of Robotic Swarms Through Informed Robots. In: Cañamero, L., Gaussier, P., Wilson, M., Boucenna, S., Cuperlier, N. (eds) From Animals to Animats 16. SAB 2022. Lecture Notes in Computer Science(), vol 13499. Springer, Cham. https://doi.org/10.1007/978-3-031-16770-6_16

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  • DOI: https://doi.org/10.1007/978-3-031-16770-6_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-16769-0

  • Online ISBN: 978-3-031-16770-6

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