Fast Reconfiguration for Programmable Matter
Irina Kostitsyna, Tom Peters, Bettina Speckmann · arXiv · 2022
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.
Plain English summary
Why this matters
Key findings
- Introduces a new shape reconfiguration approach for the amoebot model under strong per-particle constraints.
- Claims the first algorithm for amoebots that does not use a canonical intermediate configuration for arbitrary shape transformations.
- Defines new geometric primitives for amoebots to enable reconfiguration.
- States a worst-case linear number of activation rounds for reconfiguration.
- Uses the symmetric difference between input and output shapes to minimize unnecessary disassembly/reassembly when differences are small.
Limitations
The abstract does not report experimental validation, physical material implementation, or performance beyond algorithmic claims (e.g., no hardware results, no real-world constraints). It also does not specify quantitative metrics beyond activation rounds and qualitative use of symmetric difference.
Publication
- Publisher
- arXiv
- Publication date
- February 23, 2022
- Research type
- Preprint
- arXiv
- 2202.11663
- Access
- open
Tags
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