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phi Clust: Pheromone-based Aggregation for Robotic Swarms

Arvin, Farshad
Turgut, Ali Emre
Krajnik, Tomas
Rahimi, Salar
Okay, Ilkin Ege
Yue, Shigang
Watson, Simon
Lennox, Barry
In this paper, we proposed a pheromone-based aggregation method based on the state-of-the-art BEECLUST algorithm. We investigated the impact of pheromone-based communication on the efficiency of robotic swarms to locate and aggregate at areas with a given cue. In particular, we evaluated the impact of the pheromone evaporation and diffusion on the time required for the swarm to aggregate. In a series of simulated and real-world evaluation trials, we demonstrated that augmenting the BEECLUST method with artificial pheromone resulted in faster aggregation times.