School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
School of Physics, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Science. 2018 Aug 17;361(6403):672-677. doi: 10.1126/science.aan3891.
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.
成群结队的相互作用的活性粒子、昆虫或人类可以形成阻碍集体目标的集群；因此，开发控制这种堵塞的强大策略至关重要，尤其是在封闭的环境中。我们的生物和机器人挖掘实验，以及计算和理论模型的支持，揭示了个体闲置和后退可以在狭窄隧道的限制内稳健地优化挖掘性能。从密集颗粒集合体研究中获得的工具阐明了闲置如何降低堵塞的频率，以及有选择地后退如何减少仍然发生的罕见集群的溶解时间。我们的研究结果表明，在没有复杂的传感、规划和对集体的全局控制的情况下，密集的活性物质和群体可以采取策略来完成任务。
