Abstract
In this paper, we compare different aggregation strategies for cue-based aggregation with a mobile robot swarm. We used a sound source as the cue in the environment and performed real robot and simulation based experiments. We compared the performance of two proposed aggregation algorithms we called as the vector averaging and naïve with the state-of-the-art cue-based aggregation strategy BEECLUST. We showed that the proposed strategies outperform BEECLUST method. We also illustrated the feasibility of the method in the presence of noise. The results showed that the vector averaging algorithm is more robust to noise when compared to the naïve method.
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Arvin, F., Turgut, A.E., Bellotto, N., Yue, S. (2014). Comparison of Different Cue-Based Swarm Aggregation Strategies. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8794. Springer, Cham. https://doi.org/10.1007/978-3-319-11857-4_1
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DOI: https://doi.org/10.1007/978-3-319-11857-4_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11856-7
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