ATI: Assemble topological interaction overcomes consistency–cohesion trade‐off in bird flocking

In nature, various animal groups like bird flocks display proficient collective navigation achieved by maintaining high consistency and cohesion simultaneously. Both metric and topological interactions have been explored to ensure high consistency among groups. The topological interactions found in...

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Veröffentlicht in:IET cyber-systems and robotics 2024-06, Vol.6 (2), p.n/a
Hauptverfasser: Huang, Jialei, Zhu, Bo, Hu, Tianjiang
Format: Artikel
Sprache:eng
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Zusammenfassung:In nature, various animal groups like bird flocks display proficient collective navigation achieved by maintaining high consistency and cohesion simultaneously. Both metric and topological interactions have been explored to ensure high consistency among groups. The topological interactions found in bird flocks are more cohesive than metric interactions against external perturbations, especially the spatially balanced topological interaction (SBTI). However, it is revealed that in complex environments, pursuing cohesion via existing interactions compromises consistency. The authors introduce an innovative solution, assemble topological interaction, to address this challenge. Contrasting with static interaction rules, the new interaction empowers individuals with self‐awareness to adapt to the complex environment by switching between interactions through visual cues. Most individuals employ high‐consistency k‐nearest topological interaction when not facing splitting threats. In the presence of such threats, some switch to the high‐cohesion SBTI to avert splitting. The assemble topological interaction thus transcends the limit of the trade‐off between consistency and cohesion. In addition, by comparing groups with varying degrees of these two features, the authors demonstrate that group effects are vital for efficient navigation led by a minority of informed agents. Finally, the real‐world drone‐swarm experiments validate the applicability of the proposed interaction to artificial robotic collectives.
ISSN:2631-6315
2631-6315
DOI:10.1049/csy2.12114