Abstract
Self-organized aggregation is a well studied behavior in swarm robotics as it is the pre-condition for the development of more advanced group-level responses. In this paper, we investigate the design of decentralized algorithms for a swarm of heterogeneous robots that self-aggregate over distinct target sites. A previous study has shown that including as part of the swarm a number of informed robots can steer the dynamic of the aggregation process to a desirable distribution of the swarm between the available aggregation sites. We have replicated the results of the previous study using a simplified approach: we removed constraints related to the communication protocol of the robots and simplified the control mechanisms regulating the transitions between states of the probabilistic controller. The results show that the performances obtained with the previous, more complex, controller can be replicated with our simplified approach which offers clear advantages in terms of portability to the physical robots and in terms of flexibility. That is, our simplified approach can generate self-organized aggregation responses in a larger set of operating conditions than what can be achieved with the complex controller.
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Notes
- 1.
The parameters \(\alpha \) and \(\beta \) have been fine-tuned to achieve a symmetry-breaking behavior in a homogeneous swarm of \(N=100\) non-informed robots using the same arena setup illustrated in [13].
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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). A. Reina and M. Birattari 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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Sion, A., Reina, A., Birattari, M., Tuci, E. (2022). Controlling Robot Swarm Aggregation Through a Minority of Informed Robots. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2022. Lecture Notes in Computer Science, vol 13491. Springer, Cham. https://doi.org/10.1007/978-3-031-20176-9_8
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