Transforming shapes: the art of computational engineering

Researchers from the University of Luxembourg, the Institute of Fundamental Technological Research in Poland and the Franche-Comté Electronics Mechanics Thermal Science and Optics in France are working on a shape-shifting robotic material able to transform into any shape or machine.

Shape-shifting creatures or machines have inspired sci-fi literature and movies for decades. In the majority of examples, the common superior capabilities of shape-shifters are their adaptability to external environments or tasks and their tolerance to damage. But what are shape-shifting materials and how to make them?

Pursuing his own interdisciplinary project on shape-shifting modular-robotic meta-materials, Dr. Jakub Lengiewicz joined the team of Prof. Stéphane Bordas at the University of Luxembourg in 2019 with a H2020 Marie Skłodowska-Curie Actions Fellowship to investigate shape-shifting processes. “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”, comments Jakub.

Fig. 1 Shape-shifting: a cup turns into a plate. Courtesy of Prof. Julien Bourgeois and Prof. Benoît Piranda, UBFC, FEMTO-ST Institute, CNRS.

In the project Mechanics of Programmable Matter (MOrPhEM), 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). The goal is to appropriately design and programme the collective to achieve efficient and structurally-safe transformations of its shape. 

When shape-shifting proceeds, the structure may experience a mechanical failure. Just like any other structure, the modular robot may break or turn over if it is not properly balanced. To avoid such situations, the modules must be able to collectively predict dangerous moves. In collaboration with Dr. Paweł Hołobut from the Institute of Fundamental Technological Research of the Polish Academy of Sciences (IPPT PAN), and Prof. Julien Bourgeois and Prof. Benoit Piranda from the Franche-Comté Electronics Mechanics Thermal Science and Optics – Sciences and Technologies (FEMTO-ST), Dr. Jakub Lengiewicz proposed a computational approach to this problem.

Fig. 2 Modules predict possible breakage after addition of new modules; red indicates expected failure. Top row: simulations in the VisibleSim simulator. Bottom row: experiments on the Blinky Blocks robotic modules (in the rightmost figure, the robot is additionally supported to avoid the expected breakage). Courtesy of Prof. Julien Bourgeois and Prof. Benoît Piranda, UBFC, FEMTO-ST Institute, CNRS.

The first results are encouraging: “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. We demonstrated that the expected execution time of the algorithm grows extremely fast with the number of constituent robotic modules, and accordingly we proposed possible improvements to overcome this efficiency bottleneck. The scalability of such distributed algorithms is a very timely topic, additionally stimulated by the recent advances in miniaturisation of robotic modules, made by the Programmable Matter consortium”, explains Jakub.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement N°800150.