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Improving the synchronization speed of self-propelled particles with restricted vision via randomly changing the line of sight

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Abstract

In recent years, the well-developed Vicsek model (VM) has attracted more and more attention. In this paper, a novel modified VM is proposed in order to describe the collective motion of the self-propelled particles, wherein the particles have the restricted visual field and the changing line of sight (LoS). The attention field (or field of view) of each particle is a sector, and the LoS direction randomly changes around the direction of motion, in which the changing ruler follows the normal distribution. Compared with the original Vicsek model, the proposed model is more close to the reality. Simulations are performed, and the results show that the proposed modified model can accelerate the synchronization speed and enhance the robustness.

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Acknowledgements

This research is partially supported by the China Postdoctoral Science Foundation under Grant #71002011201601, the 2017 BJUT United Grand Scientific Research Program on Intelligent Manufacturing under Grant #040000546317552 and the General Program of Science and Technology Development Project of Beijing Municipal Education Commission under Grant #KM201510005005.

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Authors and Affiliations

  1. Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, People’s Republic of China

    Xiangyin Zhang, Songmin Jia & Xiuzhi Li

  2. Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing, 100124, People’s Republic of China

    Xiangyin Zhang, Songmin Jia & Xiuzhi Li

  3. Engineering Research Center of Digital Community, Ministry of Education, Beijing, 100124, People’s Republic of China

    Xiangyin Zhang, Songmin Jia & Xiuzhi Li

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  1. Xiangyin Zhang
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  2. Songmin Jia
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  3. Xiuzhi Li
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Correspondence to Xiangyin Zhang.

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Zhang, X., Jia, S. & Li, X. Improving the synchronization speed of self-propelled particles with restricted vision via randomly changing the line of sight. Nonlinear Dyn 90, 43–51 (2017). https://doi.org/10.1007/s11071-017-3644-5

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  • DOI: https://doi.org/10.1007/s11071-017-3644-5

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