Searcharxiv⌕ Search

arXiv subjects

Robert Gmyr

Publications and source records attributed to Robert Gmyr.

20 records · Page 2Linked to original sources

Infinite Object Coating in the Amoebot Model

The term programmable matter refers to matter which has the ability to change its physical properties (shape, density, moduli, conductivity, optical properties, etc.) in a programmable fashion, based upon user input or autonomous sensing. This has many applications like smart materials, autonomous monitoring and repair, and minimal invasive surgery. While programmable matter might have been considered pure science fiction more than two decades ago, in recent years a large amount of research has been conducted in this field. Often programmable matter is envisioned as a very large number of small locally interacting computational particles. We propose the Amoebot model, a new model which builds upon this vision of programmable matter. Inspired by the behavior of amoeba, the Amoebot model offers a versatile framework to model self-organizing particles and facilitates rigorous algorithmic research in the area of programmable matter. We present an algorithm for the problem of coating an infinite object under this model, and prove the correctness of the algorithm and that it is work-optimal.

cs.ET↗

Ameba-inspired Self-organizing Particle Systems

Particle systems are physical systems of simple computational particles that can bond to neighboring particles and use these bonds to move from one spot to another (non-occupied) spot. These particle systems are supposed to be able to self-organize in order to adapt to a desired shape without any central control. Self-organizing particle systems have many interesting applications like coating objects for monitoring and repair purposes and the formation of nano-scale devices for surgery and molecular-scale electronic structures. While there has been quite a lot of systems work in this area, especially in the context of modular self-reconfigurable robotic systems, only very little theoretical work has been done in this area so far. We attempt to bridge this gap by proposing a model inspired by the behavior of ameba that allows rigorous algorithmic research on self-organizing particle systems.

cs.DC↗