Format

Send to

Choose Destination
Science. 2018 Aug 17;361(6403):672-677. doi: 10.1126/science.aan3891.

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

Author information

1
School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
2
School of Physics, Georgia Institute of Technology, Atlanta, GA 30332, USA.
3
School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
4
Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Str. 38, 01187 Dresden, Germany.
5
Department of Physics, University of Colorado Boulder, Boulder, CO 80309, USA.
6
School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.
7
School of Physics, Georgia Institute of Technology, Atlanta, GA 30332, USA. daniel.goldman@physics.gatech.edu.
#
Contributed equally

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.

PMID:
30115804
DOI:
10.1126/science.aan3891

Supplemental Content

Full text links

Icon for HighWire
Loading ...
Support Center