The Structural Power of Reconfigurable Circuits in the Amoebot Model

TL;DR

This paper explores the reconfigurable circuit extension of the amoebot model, demonstrating its ability to efficiently solve fundamental problems like shape analysis and symmetry detection in programmable matter.

Contribution

It introduces the structural power of reconfigurable circuits in the amoebot model, enabling polylogarithmic-time solutions to key problems in shape transformation and structural analysis.

Findings

Polylogarithmic-time solutions for fundamental problems

Ability to identify axes and maximum points in amoebot structures

Construction of canonical paths and spanning trees

Abstract

The amoebot model [Derakhshandeh et al., 2014] has been proposed as a model for programmable matter consisting of tiny, robotic elements called amoebots. We consider the reconfigurable circuit extension [Feldmann et al., JCB 2022] of the geometric (variant of the) amoebot model that allows the amoebot structure to interconnect amoebots by so-called circuits. A circuit permits the instantaneous transmission of signals between the connected amoebots. In this paper, we examine the structural power of the reconfigurable circuits. We start with some fundamental problems like the stripe computation problem where, given any connected amoebot structure $S$, an amoebot $u$ in $S$, and some axis $X$, all amoebots belonging to axis $X$ through $u$ have to be identified. Second, we consider the global maximum problem, which identifies an amoebot at the highest possible position with respect to some direction in some given amoebot (sub)structure. A solution to this problem can then be used to solve the skeleton problem, where a (not necessarily simple) cycle of amoebots has to be found in the given amoebot structure which contains all boundary amoebots. A canonical solution to that problem can then be used to come up with a canonical path, which provides a unique characterization of the shape of the given amoebot structure. Constructing canonical paths for different directions will then allow the amoebots to set up a spanning tree and to check symmetry properties of the given amoebot structure. The problems are important for a number of applications like rapid shape transformation, energy dissemination, and structural monitoring. Interestingly, the reconfigurable circuit extension allows polylogarithmic-time solutions to all of these problems.