Supplementary Materials

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

J. Aguilar, D. Monaenkova, V. Linevich, W. Savoie, B. Dutta, H.-S. Kuan, M. D. Betterton, M. A. D. Goodisman, D. I. Goldman

Materials/Methods, Supplementary Text, Tables, Figures, and/or References

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  • Materials and Methods 
  • Figs. S1 to S26 
  • Tables S1 to S4 
  • Captions for Movies S1 to S5 
  • References 

Images, Video, and Other Media

Movie S1
Ant activity experiments: Video of an ant (yellow-orange) giving up/reversing when faced with heavy traffic in tunnel.
Movie S2
Ant simulation: Animation of a Cellular Automata (CA) simulation of ants with Active protocol (equal workload distribution) vs. Lorenz protocol (unequal workload). Cell colors denote soil (light grey), tunnel (white). CA ants moving towards the excavation site (orange) and exiting the tunnel (dark grey).
Movie S3
Single robot excavation: Video of a robophysical excavator following a pink line (a guidance trail) and excavating model cohesive granular media; the plastic hollow shells are filled with loose magnets enabling clumps to form.
Movie S4
Collective clogging in robot excavation: Video of robophysical excavators encountering and resolving a clog while excavating model cohesive granular media.
Movie S5
Robophysical experiments comparing excavation protocols: Video comparing Active (top), Reversal (middle) and Lorenz (bottom) protocols implemented on excavating robots. Each Active robot exhibited maximum levels of activity. Reversal robots had a small probability to abandon the excavation attempt if the excavation area could not be reached within pre-defined time interval. Each Lorenz robot was assigned a distinct probability to re-enter tunnel after excavation. The proportion of idle and active robots is similar to observations of ant behavior.