An experimental platform encodes multiple programmable persistent random walks in active Brownian particles and demonstrates their effect on emergent clustering.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
Greedy Kalman-Swarm lets individual robots improve state estimates by greedily fusing available neighbor relative sensing data, yielding better swarm accuracy than independent filters while remaining functional under missing data.
citing papers explorer
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Programmable Persistent Random Walks in Active Brownian Particles Govern Emergent Dynamics
An experimental platform encodes multiple programmable persistent random walks in active Brownian particles and demonstrates their effect on emergent clustering.
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Greedy Kalman-Swarm: Improving State Estimation in Robot Swarms in Harsh Environments
Greedy Kalman-Swarm lets individual robots improve state estimates by greedily fusing available neighbor relative sensing data, yielding better swarm accuracy than independent filters while remaining functional under missing data.