TY - GEN
T1 - Self-organized Flocking in Three Dimensions
AU - Karagüzel, Tugay Alperen
AU - van Diggelen, Fuda
AU - Rincon, Andres Garcia
AU - Ferrante, Eliseo
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - This paper introduces a novel methodology for achieving self-organized flocking behavior entirely in three dimensions, building upon the active elastic model. Through comprehensive evaluations made with kinematic and dynamic simulations, as well as through a real-world implementation with Crazyflie nano drones, we demonstrate the feasibility and robustness of our approach under various operational constraints. Our findings show that the system scalability to larger swarm sizes has a stronger dependence to parameters, in particular to the strength of the formation, compared to the two dimensional counterpart. The successful deployment of this methodology in an indoor environment, where the system navigates physical boundaries and demonstrates cohesive and ordered motion, showcases its potential applications in surveillance, search and rescue, and environmental monitoring. This work paves the way for future research in advanced swarm behaviors and underscores the practical applicability of three-dimensional flocking in robotic swarms.
AB - This paper introduces a novel methodology for achieving self-organized flocking behavior entirely in three dimensions, building upon the active elastic model. Through comprehensive evaluations made with kinematic and dynamic simulations, as well as through a real-world implementation with Crazyflie nano drones, we demonstrate the feasibility and robustness of our approach under various operational constraints. Our findings show that the system scalability to larger swarm sizes has a stronger dependence to parameters, in particular to the strength of the formation, compared to the two dimensional counterpart. The successful deployment of this methodology in an indoor environment, where the system navigates physical boundaries and demonstrates cohesive and ordered motion, showcases its potential applications in surveillance, search and rescue, and environmental monitoring. This work paves the way for future research in advanced swarm behaviors and underscores the practical applicability of three-dimensional flocking in robotic swarms.
UR - http://www.scopus.com/inward/record.url?scp=85205123406&partnerID=8YFLogxK
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U2 - 10.1007/978-3-031-70932-6_12
DO - 10.1007/978-3-031-70932-6_12
M3 - Conference contribution
AN - SCOPUS:85205123406
SN - 9783031709319
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 155
EP - 167
BT - Swarm Intelligence - 14th International Conference, ANTS 2024, Proceedings
A2 - Hamann, Heiko
A2 - Reina, Andreagiovanni
A2 - Kuckling, Jonas
A2 - Buss, Eduard
A2 - Dorigo, Marco
A2 - Pérez Cáceres, Leslie
A2 - Kaiser, Tanja Katharina
A2 - Soorati, Mohammad
A2 - Hasselmann, Ken
PB - Springer Science and Business Media Deutschland GmbH
T2 - 14th International Conference on Swarm Intelligence, ANTS 2024
Y2 - 9 October 2024 through 11 October 2024
ER -