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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Comparison of Different Cue-Based Swarm Aggregation Strategies
verfasst von : Farshad Arvin, Ali Emre Turgut, Nicola Bellotto, Shigang Yue
Erschienen in: Advances in Swarm Intelligence
Verlag: Springer International Publishing
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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.