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Hybrid Coordinating Algorithm for Flying Robots

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Abstract

Positioning of flying swarm robots is an interesting research area because the global behaviors must emerge from many diverse local interactions. A central issue in coordinating of swarm is enabling robots to take emergence formation by collective behavior. This paper describes a hybrid coordinating algorithm using pheromone for controlling a swarm of identical flying robots to spatially self-organize into arbitrary shapes using local communication maintaining a certain level of density. The proposed approach considers the topological structure of the organization, supports dynamic reconfiguration and self-organization.

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Acknowledgments

This work was supported by a 2017 research grant from Youngsan University, Republic of Korea.

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Authors and Affiliations

  1. Department of Intelligent Robotics, Youngsan University, Yangsan, Korea

    Kiwon Yeom

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  1. Kiwon Yeom
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Correspondence to Kiwon Yeom .

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Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Politecnico di Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. University of Wollongong, North Wollongong, New South Wales, Australia

    Prashan Premaratne

  4. Indian Institute of Technology, Kanpur, India

    Phalguni Gupta

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Yeom, K. (2017). Hybrid Coordinating Algorithm for Flying Robots. In: Huang, DS., Bevilacqua, V., Premaratne, P., Gupta, P. (eds) Intelligent Computing Theories and Application. ICIC 2017. Lecture Notes in Computer Science(), vol 10361. Springer, Cham. https://doi.org/10.1007/978-3-319-63309-1_14

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  • DOI: https://doi.org/10.1007/978-3-319-63309-1_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63308-4

  • Online ISBN: 978-3-319-63309-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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