Collective clog control: Optimizing traffic flow in confined biological and robophysical excavation
Collective clog control: Optimizing traffic flow in confined biological and robophysical excavation
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DOI：
10.1126/science.aan3891
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发表时间：
2018-08-17
期刊：
影响因子：
56.9
通讯作者：
Goldman, D. I.
中科院分区：
文献类型：
--
作者：
Aguilar, J.;Monaenkova, D.;Goldman, D. I.
相互作用的活性颗粒，昆虫或人类的组可以形成簇，以阻碍集体的目标。因此，制定控制此类堵塞的强大策略至关重要，尤其是在狭窄的环境中。我们的生物学和机器人物理发掘实验得到了计算和理论模型的支持，表明可以通过单个闲置和撤退在狭窄的隧道的约束中进行良好的优化挖掘性能。研究密集颗粒的研究中的工具阐明了闲置的闲置堵塞频率以及选择性撤退如何减少仍在发生的罕见群集的群集溶解时间。我们的结果表明，在没有复杂的感应，计划和集体的全球控制的情况下，密集的积极物质和群体可以成为任务的策略。
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.