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Collective clog control: Optimizing traffic flow in confined biological and robophysical excavation

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Kuan,  Hui-Shun
Max Planck Institute for the Physics of Complex Systems, Max Planck Society;

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Aguilar, J., Monaenkova, D., Linevich, V., Savoie, W., Dutta, B., Kuan, H.-S., et al. (2018). Collective clog control: Optimizing traffic flow in confined biological and robophysical excavation. Science, 361(6403), 672-677. doi:10.1126/science.aan3891.


Cite as: http://hdl.handle.net/21.11116/0000-0002-66A2-4
Abstract
Groups of interacting active particles, insects, or humans can form clusters that hinder the goals of the collective; therefore, development of robust strategies for control of such clogs is essential, particularly in confined environments. Our biological and robophysical excavation experiments, supported by computational and theoretical models, reveal that digging performance can be robustly optimized within the constraints of narrow tunnels by individual idleness and retreating. Tools from the study of dense particulate ensembles elucidate how idleness reduces the frequency of flow-stopping clogs and how selective retreating reduces cluster dissolution time for the rare clusters that still occur. Our results point to strategies by which dense active matter and swarms can become task capable without sophisticated sensing, planning, and global control of the collective.