Sublinear-Time Reconfiguration of Programmable Matter with Joint Movements

Manish Kumar, Othon Michail, Andreas Padalkin, Christian Scheideler · arXiv · 2026

The paper shows sublinear-time centralized reconfiguration of geometric amoebot programmable matter using joint parallel movements, including universal reconfiguration to a line segment in O(√n log n) rounds.

Moderate AI ConfidenceGood SourceSimulationReadiness Unknown

Plain English summary

The paper studies how a group of small robots (“amoebots”) that occupy grid nodes can change shape through expansion and contraction operations. It focuses on a “joint movement” extension where multiple amoebots can move in parallel to coordinate larger substructures. The authors examine centralized reconfiguration algorithms for geometric amoebot structures, aiming to reconfigure any structure from one class into some structure in another class. They specifically target sublinear-time algorithms. They answer an open question by proving that any structure can be reconfigured into a canonical line-segment structure in O(√n log n) rounds, without relying on extra assumptions used in prior work. They also provide a constant-time method to reconfigure any spiral structure into a line segment, enabled by new constant-time movement primitives.

Why this matters

It proves sublinear-time universal reconfiguration within the joint movement amoebot model without auxiliary assumptions (unlike prior work), and adds constant-time primitives for parallel movement. The abstract presents algorithmic results (reconfiguration schedules and time bounds) and does not provide evidence of physical prototypes, field testing, or commercialization.

Key findings

  • Centralized reconfiguration is studied for geometric amoebot structures under a joint movement model.
  • Any structure can be reconfigured into a canonical line-segment structure in O(√n log n) rounds.
  • Any spiral structure can be reconfigured into a line segment in constant time.
  • New constant-time primitives enable efficient parallel movement in the joint movement model.
  • The results demonstrate sublinear reconfiguration without auxiliary assumptions (e.g., metamodules) used previously.

Limitations

The abstract restricts attention to centralized algorithms and states that distributed solutions are left for future work; it also notes an open question about achieving universal reconfiguration in polylogarithmic or constant time.

Publication

Publisher
arXiv
Publication date
March 11, 2026
Research type
Preprint
arXiv
2603.10720
Access
open

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Method note: Summaries and ratings on this page are generated by AI from the abstract only. Read the original paper for full context. · Model: gpt-5.4-nano-2026-03-17