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Mechanics of Programmable Matter

Periodic Reporting for period 1 - MOrPhEM (Mechanics of Programmable Matter)

Okres sprawozdawczy: 2019-03-01 do 2021-02-28

The general interest of the project is on a shape-shifting robotic material able to transform into any shape or machine. In the majority of examples, the common superior capabilities of the shape-shifters are their adaptability to external environments or tasks and their tolerance to damage. The foreseeable application domains of shape-shifters seem as futuristic as the technology itself. Try to imagine a future computer game in which you can physically interact with avatars of other online players. In medicine, a shape-shifting material could be injected into the bloodstream, enter the desired areas in organs and treat them. Such adaptable, multi-functional, shape-shifting devices are indeed exciting prospects which could change the way we interact with the world around us. Yet they are still in their infancy, and we remain unable to predict which of the exciting potential applications are actually achievable.
In this project, the shape-shifters, also known as programmable matter, are viewed as structures composed of interconnected, microscopic, active robotic modules, which are able to process and exchange information, reconnect and move with respect to their neighbours. As such, they compose a computing network of continuously changing connection topology, which must collectively decide how to physically reorganise (similarly to fire-ants, which can form engineering structures from their bodies). One of the obstacles for them to freely reorganise is that, when shape-shifting proceeds, these physical computing collectives may experience a mechanical failure. Just like any other structure, a modular robot may break or turn over if it is not properly balanced. The goal of this project is to appropriately design and programme the collective to achieve both: structurally-safe and efficient transformations of its shape.
To avoid mechanical failures, the modules must be able to collectively predict dangerous moves. In collaboration with the Institute of Fundamental Technological Research of the Polish Academy of Sciences (IPPT PAN), and the Franche-Comté Electronics Mechanics Thermal Science and Optics – Sciences and Technologies (FEMTO-ST), we proposed a computational approach to this problem. We developed a distributed computational algorithm that allows shape-shifters to predict if a planned reconfiguration step is structurally safe, i.e. whether it will not cause the modular robot to break or turn over. The scheme has been validated both on a virtual test bed (an emulator of a shape-shifter), as well as on the real reconfigurable modular robot Blinky Blocks.
Although we physically demonstrated that the abovementioned scheme is capable of predicting mechanical failures for a variety of modular robotic structures, we also showed that the expected execution time of the algorithm grows extremely fast with the number of constituent robotic modules. Accordingly, with IPPT PAN, we developed an improved algorithm that partially reduces this efficiency bottleneck. This improved algorithm has been then validated on a simulator.
In order to transform shapes efficiently, a modular robot must form a special porous frame. This allows the remaining modules to reorganise in parallel across the robot’s volume (similar to water flowing through a foam). With FEMTO-ST, we are designing generic algorithms to guide that flow, which should be compatible with many existing- and possibly many future designs of modular robots.
The results of this project were disseminated in peer-reviewerd journals and conferences, as well as in the form of popular-science communications/articles.
The scalability of such distributed algorithms and reconfiguration schemes is a very timely topic, additionally stimulated by the recent advances in miniaturisation of robotic modules. The new 3.6mm-wide spherical module (3D catom), being currently developed in FEMTO-ST, is currently the world’s smallest design of this kind. Even a handful of these modules count hundreds of units, and will require algorithms developed in this project to act efficiently.
One of beneficial effect of this project is the close collaboration that has been established between the teams from the University of Luxembourg, IPPT PAN and FEMTO-ST, as a part of the Programmable Matter consortium (https://www.programmable-matter.com/). This promises practical application of the results of this project and possible future commercialization.
Modules compute stresses at inter-modular connections; red indicates expected failure.
Modules compute stability condition; purple indicates expected failure.