TY - JOUR
T1 - Programming active cohesive granular matter with mechanically induced phase changes
AU - Li, Shengkai
AU - Dutta, Bahnisikha
AU - Cannon, Sarah
AU - Daymude, Joshua J.
AU - Avinery, Ram
AU - Aydin, Enes
AU - Richa, Andréa W.
AU - Goldman, Daniel I.
AU - Randall, Dana
N1 - Publisher Copyright:
© 2021 The Authors, some rights reserved.
PY - 2021/4/21
Y1 - 2021/4/21
N2 - At the macroscale, controlling robotic swarms typically uses substantial memory, processing power, and coordina tion unavailable at the microscale, e.g., for colloidal robots, which could be useful for fighting disease, fabricating intelligent textiles, and designing nanocomputers. To develop principles that can leverage physical interactions and thus be used across scales, we take a two-pronged approach: A theoretical abstraction of self-organizing parti cle systems and an experimental robot system of active cohesive granular matter that intentionally lacks digital electronic computation and communication, using minimal (or no) sensing and control. As predicted by theory, as interparticle attraction increases, the collective transitions from dispersed to a compact phase. When aggregated, the collective can transport non-robot "impurities,"thus performing an emergent task driven by the physics under lying the transition. These results reveal a fruitful interplay between algorithm design and active matter robophys ics that can result in principles for programming collectives without the need for complex algorithms or capabilities.
AB - At the macroscale, controlling robotic swarms typically uses substantial memory, processing power, and coordina tion unavailable at the microscale, e.g., for colloidal robots, which could be useful for fighting disease, fabricating intelligent textiles, and designing nanocomputers. To develop principles that can leverage physical interactions and thus be used across scales, we take a two-pronged approach: A theoretical abstraction of self-organizing parti cle systems and an experimental robot system of active cohesive granular matter that intentionally lacks digital electronic computation and communication, using minimal (or no) sensing and control. As predicted by theory, as interparticle attraction increases, the collective transitions from dispersed to a compact phase. When aggregated, the collective can transport non-robot "impurities,"thus performing an emergent task driven by the physics under lying the transition. These results reveal a fruitful interplay between algorithm design and active matter robophys ics that can result in principles for programming collectives without the need for complex algorithms or capabilities.
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U2 - 10.1126/sciadv.abe8494
DO - 10.1126/sciadv.abe8494
M3 - Article
C2 - 33893101
AN - SCOPUS:85104958562
SN - 2375-2548
VL - 7
JO - Science Advances
JF - Science Advances
IS - 17
M1 - eabe8494
ER -