Comparison of Different Cue-Based Swarm Aggregation Strategies

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8794)


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.


swarm robotics collective behavior cue-based aggregation 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Computational Intelligence Lab (CIL), School of Computer ScienceUniversity of LincolnLincolnUK
  2. 2.Laboratory of Socioecology and Social EvolutionKU LeuvenLeuvenBelgium

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