TY - GEN
T1 - Controlling Robot Swarm Aggregation Through a Minority of Informed Robots
AU - Sion, Antoine
AU - Reina, Andreagiovanni
AU - Birattari, Mauro
AU - Tuci, Elio
N1 - Publisher Copyright:
© 2022, Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - swarm robotics
KW - self-organised aggregation
KW - heterogeneous swarm
KW - finite-state machine
UR - http://www.scopus.com/inward/record.url?scp=85138781757&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-20176-9_8
DO - 10.1007/978-3-031-20176-9_8
M3 - Conference contribution
AN - SCOPUS:85138781757
SN - 9783031201752
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 91
EP - 103
BT - Swarm Intelligence - 13th International Conference, ANTS 2022, Proceedings
A2 - Dorigo, Marco
A2 - Strobel, Volker
A2 - Camacho-Villalón, Christian
A2 - Hamann, Heiko
A2 - Hamann, Heiko
A2 - López-Ibáñez, Manuel
A2 - García-Nieto, José
A2 - Engelbrecht, Andries
A2 - Pinciroli, Carlo
PB - Springer Science and Business Media Deutschland GmbH
T2 - 13th International Conference on Swarm Intelligence, ANTS 2022
Y2 - 2 November 2022 through 4 November 2022
ER -