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