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Heterogeneity-driven collective-motion patterns of active gels

Rui Teng, Qingyu Gao, Ling Yuan, Lin Ren, Jing Wang, Yunjie Wang, Irving R. Epstein

Year
2022
Citations
8

Abstract

Biological swarms produce movement patterns that enhance their viability and functionality. We investigate the importance of internal heterogeneity within a group for the generation and transformation of group movement patterns. We find that an increase in the activity difference between a pair of chemically reactive gels and the rest causes the gel group to evolve from irregular random motion to ordered periodic swing-forward and circular motions. Our results imply that internal heterogeneity within a group is a key factor in generating ordered motion patterns, such as linear or curved locomotion, and disperse or compact population distributions. Dynamical analysis of collective pattern transitions reveals that the location and level of activity of a few “leaders” act as control parameters for bifurcations of collective-motion patterns. Our results suggest a possible origin of swarm motion patterns and may also be used to tailor robot swarms to enhance flexibility and robustness.

Keywords

Motion (physics)Collective motionComputer scienceComputer visionArtificial intelligence

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