Universal Coating by 3D Hybrid Programmable Matter

TL;DR

This paper presents an optimal algorithm for 3D hybrid programmable matter to coat surfaces with passive tiles, inspired by nano-robot applications, achieving worst-case efficiency with limited agent capabilities.

Contribution

It introduces a universal coating algorithm for 3D hybrid programmable matter that is optimal in worst-case steps and works with limited agent memory and sensing.

Findings

Algorithm requires O(n^2) steps, which is worst-case optimal.

Effective on restricted graphs with a single tile type.

Extended to encode complex surface graphs with multiple tile types.

Abstract

Motivated by the prospect of nano-robots that assist human physiological functions at the nanoscale, we investigate the coating problem in the three-dimensional model for hybrid programmable matter. In this model, a single agent with strictly limited viewing range and the computational capability of a deterministic finite automaton can act on passive tiles by picking up a tile, moving, and placing it at some spot. The goal of the coating problem is to fill each node of some surface graph of size $n$ with a tile. We first solve the problem on a restricted class of graphs with a single tile type, and then use constantly many tile types to encode this graph in certain surface graphs capturing the surface of 3D objects. Our algorithm requires $\mathcal{O}(n^2)$ steps, which is worst-case optimal compared to an agent with global knowledge and no memory restrictions.