Abstract
Although the use of “pheromones” in coordinating swarm robotic tasks such as foraging, coverage, and exploration is common, its use in aggregation still needs further exploration. In this paper, we introduce a pheromone-based aggregation (PBA) algorithm that extends BEECLUST, which uses an environmental cue, such as temperature, to regulate the aggregation of agents. We use pheromones for guidance, laid dynamically by the agents in the form of trails to aid the aggregation process by expanding the region of attraction. Through systematic simulations of the Kobot mobile platform, we show that PBA achieves a higher performance, measured by the Normalized Aggregation Size, than the BEECLUST algorithm in environments where the relative size of the cue within the environment is small and the robot density is low.
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Notes
- 1.
Sample experiments can be found in https://tinyurl.com/5d6wk4jx.
- 2.
Source code available in https://tinyurl.com/r5vamjhx.
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This paper is partially supported by METU ADEP-302-2024-11468.
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Botasun, A., Şahin, M., Turgut, A.E., Şahin, E. (2024). Development of a Pheromone-Based Aggregation Method for Swarm Robots. In: Hamann, H., et al. Swarm Intelligence. ANTS 2024. Lecture Notes in Computer Science, vol 14987. Springer, Cham. https://doi.org/10.1007/978-3-031-70932-6_19
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