Impact of the Sampling Time on the Aggregation of Robotic Swarms through Informed Robots

Antoine SION; Andreagiovanni Reina; Mauro Birattari; Elio Tuci

doi:10.1007/978-3-031-16770-6_16

Impact of the Sampling Time on the Aggregation of Robotic Swarms through Informed Robots

Antoine SION, Andreagiovanni Reina, Mauro Birattari, Elio Tuci

Research output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Proceedings of the 16th International Conference on the Simulation of Adaptive Behavior
Subtitle of host publication	SAB2022
Editors	Lola Canamero, Philippe Gaussier, Myra Wilson, Sofiane Baucenna, Nicolas Couperlier
Publisher	Springer
Pages	193-204
Number of pages	12
ISBN (Electronic)	978-3-031-16770-6
ISBN (Print)	978-3-031-16769-0
DOIs	https://doi.org/10.1007/978-3-031-16770-6_16
Publication status	Published - Sept 2022
Event	16th International Conference on Simulation of Adaptive Behavior - Cergy-Pontoise, France Duration: 20 Sept 2022 → 23 Sept 2022

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13499 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Simulation of Adaptive Behavior
Abbreviated title	SAB 2022
Country/Territory	France
City	Cergy-Pontoise
Period	20/09/22 → 23/09/22

Access to Document

10.1007/978-3-031-16770-6_16

Cite this

SION, A., Reina, A., Birattari, M., & Tuci, E. (2022). Impact of the Sampling Time on the Aggregation of Robotic Swarms through Informed Robots. In L. Canamero, P. Gaussier, M. Wilson, S. Baucenna, & N. Couperlier (Eds.), Proceedings of the 16th International Conference on the Simulation of Adaptive Behavior : SAB2022 (pp. 193-204). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13499 LNAI). Springer. https://doi.org/10.1007/978-3-031-16770-6_16

SION, Antoine ; Reina, Andreagiovanni ; Birattari, Mauro et al. / Impact of the Sampling Time on the Aggregation of Robotic Swarms through Informed Robots. Proceedings of the 16th International Conference on the Simulation of Adaptive Behavior : SAB2022. editor / Lola Canamero ; Philippe Gaussier ; Myra Wilson ; Sofiane Baucenna ; Nicolas Couperlier. Springer, 2022. pp. 193-204 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Impact of the Sampling Time on the Aggregation of Robotic Swarms through Informed Robots",

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.",

author = "Antoine SION and Andreagiovanni Reina and Mauro Birattari and Elio Tuci",

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SION, A, Reina, A, Birattari, M & Tuci, E 2022, Impact of the Sampling Time on the Aggregation of Robotic Swarms through Informed Robots. in L Canamero, P Gaussier, M Wilson, S Baucenna & N Couperlier (eds), Proceedings of the 16th International Conference on the Simulation of Adaptive Behavior : SAB2022. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13499 LNAI, Springer, pp. 193-204, 16th International Conference on Simulation of Adaptive Behavior, Cergy-Pontoise, France, 20/09/22. https://doi.org/10.1007/978-3-031-16770-6_16

Impact of the Sampling Time on the Aggregation of Robotic Swarms through Informed Robots. / SION, Antoine; Reina, Andreagiovanni; Birattari, Mauro et al.
Proceedings of the 16th International Conference on the Simulation of Adaptive Behavior : SAB2022. ed. / Lola Canamero; Philippe Gaussier; Myra Wilson; Sofiane Baucenna; Nicolas Couperlier. Springer, 2022. p. 193-204 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13499 LNAI).

Research output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Impact of the Sampling Time on the Aggregation of Robotic Swarms through Informed Robots

AU - SION, Antoine

AU - Reina, Andreagiovanni

AU - Birattari, Mauro

AU - Tuci, Elio

PY - 2022/9

Y1 - 2022/9

N2 - 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.

AB - 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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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Proceedings of the 16th International Conference on the Simulation of Adaptive Behavior

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ER -

SION A, Reina A, Birattari M, Tuci E. Impact of the Sampling Time on the Aggregation of Robotic Swarms through Informed Robots. In Canamero L, Gaussier P, Wilson M, Baucenna S, Couperlier N, editors, Proceedings of the 16th International Conference on the Simulation of Adaptive Behavior : SAB2022. Springer. 2022. p. 193-204. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-16770-6_16

Impact of the Sampling Time on the Aggregation of Robotic Swarms through Informed Robots

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16th International Conference on Simulation of Adaptive Behavior

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Impact of the Sampling Time on the Aggregation of Robotic Swarms through Informed Robots

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16th International Conference on Simulation of Adaptive Behavior

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