RT Conference Proceedings
T1 Distributed Coordination of Heterogeneous Robotic Swarms Using Stochastic Diffusion Search
A1 Osaba, Eneko
A1 Del Ser, Javier
A1 Jubeto, Xabier
A1 Iglesias, Andrés
A1 Fister, Iztok
A1 Gálvez, Akemi
A2 Analide, Cesar
A2 Novais, Paulo
A2 Camacho, David
A2 Yin, Hujun
AB The term Swarm Robotics collectively refers to a population of robotic devices that efficiently undertakes diverse tasks in a collaborative way by virtue of computational intelligence techniques. This paradigm has given rise to a profitable stream of contributions in recent years, all sharing a clear consensus on the performance benefits derived from the increased exploration capabilities offered by Swarm Robotics. This manuscript falls within this topic: specifically, it gravitates on an heterogeneous Swarm Robotics system that relies on Stochastic Diffusion Search (SDS) as the coordination heuristics for the exploration, location and delimitation of areas scattered over the area in which robots are deployed. The swarm is composed by agents of diverse kind, which can be ground robots or flying devices. These agents communicate to each other and cooperate towards the accomplishment of the exploration tasks comprising the mission of the overall swarm. Furthermore, maps contain several obstacles and dangers, implying that in order to enter a specific area, robots should meet certain conditions. Experiments are conducted over three different maps and three implemented solving approaches. Conclusions are drawn from the obtained results, confirming that i) SDS allows for a lightweight, heuristic mechanism for the coordination of the robots; and ii) the most efficient swarming approach is the one comprising a heterogeneity of ground and aerial robots.
PB Springer
SN 978-3-030-62365-4; 978-3-030-62364-7
SN 9783030623647
YR 2020
FD 2020-10-27
LA eng
NO Osaba , E , Del Ser , J , Jubeto , X , Iglesias , A , Fister , I & Gálvez , A 2020 , Distributed Coordination of Heterogeneous Robotic Swarms Using Stochastic Diffusion Search . in C Analide , P Novais , D Camacho & H Yin (eds) , unknown . vol. 12490 , 0302-9743 , Springer , pp. 79-91 , 21th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2020 , Guimaraes , Portugal , 4/11/20 . https://doi.org/10.1007/978-3-030-62365-4_8
NO conference
NO Publisher Copyright: © 2020, Springer Nature Switzerland AG.
DS TECNALIA Publications
RD 29 jun 2024