Modeling, analysis, and optimization of three-dimensional restricted visual field metric-free swarms

Li, Qing; Zhang, Lingwei; Jia, Yongnan; Lu, Tianzhao; Chen, Xiaojie

doi:10.1016/j.chaos.2022.111879

Cited by 4 publications

(4 citation statements)

References 46 publications

(63 reference statements)

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“…SBTI endows groups with sufficient cohesion to prevent group splitting. They also verified that another topological interaction, where the interacting neighbours are selected using Voronoi tessellation [32–36], is equivalent to the SBTI of specific parameters. In the present paper, we also test the more robust cohesion grant by topological interactions than by metric ones in complex environments.…”

Section: Introductionmentioning

confidence: 90%

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

Huang,

Zhu,

2024

IET Cyber-Syst and Robotics

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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.

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Section: Introductionmentioning

confidence: 90%

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

Huang,

Zhu,

2024

IET Cyber-Syst and Robotics

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“…Since v i,k (T ) is non-zero with respect to i, v M,k (T ) > 0 for all i ∈ I. Thus, from (21), we have…”

Section: Vector-type Rayleigh Frictionmentioning

confidence: 97%

“…We have now discussed the convergence of the velocities of the agents in System ( 20)- (21). Next, we provide estimations of the velocities, which imply asymptotic flocking.…”

Section: Vector-type Rayleigh Frictionmentioning

confidence: 99%

“…This improved understanding can also facilitate the development of more efficient engineering systems, including unmanned aerial vehicles. Consequently, various models, such as the Vicsek model, Kuramoto model, minimal model, and Cucker-Smale model, have been proposed and are being studied in different fields (see [2,3,19,20,21,24] and the references therein).…”

Section: Introductionmentioning

confidence: 99%

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