Active Matter
Non-equilibrium systems whose constituents consume energy to produce collective behaviour.
Logarithmic-Time Geodesically Convex Decomposition in Programmable Matter
It presents an O(log n)-round algorithm to decompose arbitrary amoebot programmable-matter structures into O(|H|) geodesically convex regions using reconfigurable circuits.
GRASPion: An open-source, programmable brainbot for active matter research
The GRASPion is a programmable bristlebot designed for studying active matter systems with various motion capabilities and real-time interaction.
DiffeoMorph: Learning to Morph 3D Shapes Using Differentiable Agent-Based Simulations
DiffeoMorph is an end-to-end differentiable method that learns agent-based morphogenesis rules to transform minimally patterned starts into target 3D shapes using an invariant Zernike-based shape-matching loss.
Force Characterization of Insect-Scale Aquatic Propulsion Based on Fluid-Structure Interaction
Insect-scale microrobotic swimmers with SMA-driven soft tails are force-characterized, yielding first instantaneous thrust measurements linked to fluid-structure interaction.
Single Bridge Formation in Self-Organizing Particle Systems
A mathematical analysis shows that, given strong directional and neighbor-count preferences, self-organizing particles almost certainly form exactly one bridge without central coordination.
Asynchronous Silent Programmable Matter: Line Formation
It proposes an optimal distributed algorithm for line formation in the SILBOT programmable-matter model under asynchronous, silent, oblivious particle behavior.
Adaptive Collective Responses to Local Stimuli in Anonymous Dynamic Networks
A local-interaction algorithm enables agents in programmable matter to switch system-wide phases in response to dynamically appearing/disappearing stimuli, even on reconfigurable graphs.
Local Stochastic Algorithms for Alignment in Self-Organizing Particle Systems
Local stochastic, distributed rules on lattice-based self-organizing particles can produce collective alignment (or nonalignment) and also tune compression/expansion while maintaining or relaxing connectivity constraints.
Fast Reconfiguration for Programmable Matter
A new amoebot shape-reconfiguration algorithm achieves global transformation from local rules without relying on a canonical intermediate configuration, with linear activation rounds in the worst case.
Gait learning for soft microrobots controlled by light fields
A Bayesian optimization + Gaussian-process learning scheme enables light-controlled soft microrobots to optimize and adapt gaits with few experiments and robustness across microrobot samples.