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Self-Organizing Particle Systems (SOPS)
Abstracting programmable matter using the
(canonical) amoebot model
. Developing distributed algorithms for tasks of self-organization. Rigorously analyzing these behaviors for provable guarantees on correctness, runtime, and reliability.
Andréa W. Richa
,
Christian Scheideler
,
Joshua J. Daymude
,
Erik D. Demaine
,
Irina Kostitsyna
,
Matthew J. Patitz
,
John Calvin Alumbaugh
,
Joseph L. Briones
,
Kristian Hinnenthal
,
Jamison W. Weber
,
Robert Gmyr
,
Thim Strothmann
,
Zahra Derakhshandeh
,
Alexandra Porter
,
Tishya Chhabra
GitHub
SOPSLab@ASU
Adaptive Self-Organization in Anonymous Dynamic Networks
Reimagining graph-based models for moving and interacting entities. Designing concurrent and distributed algorithms that are robust to highly dynamic environments. Coordinating anonymous entities across time-varying tasks.
Joshua J. Daymude
,
Andréa W. Richa
,
Christian Scheideler
SAND Conference
A Distributed, Stochastic Framework for Active Matter
Harnessing phase changes from statistical physics in algorithm design. Incorporating algorithmic theory in robot design and manufacturing. Making analogies between macro-scale robot swarm dynamics and the physics of granular active matter systems.
Andréa W. Richa
,
Dana Randall
,
Daniel I. Goldman
,
Sarah Cannon
,
Joshua J. Daymude
,
Ram Avinery
,
Enes Aydin
,
Bahnisikha Dutta
,
Shengkai Li
,
William Savoie
,
Ross Warkentin
,
Cem Gökmen
,
Marta Andrés Arroyo
SOPSLab@ASU
CRABLab@GaTech
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