Scientists at the University of Sheffield have significantly advanced in developing Kilobots or stretchable robotic fabrics, which can change size, shrink, and move with exceptional precision. Led by Dr. Roderich Gross from the Department of Automatic Control and Systems Engineering, the research team has successfully demonstrated the feasibility of creating intelligent robotic fabrics by coupling low-power robotic modules together through an elastic mesh.
A revolutionary breakthrough in robotic fabrics
In a groundbreaking study published in Nature Communications, the University of Sheffield researchers revealed that elastic links enabled these modular robots, roughly the size of a 50p coin, to move reliably in a coordinated manner. The study showcased the superiority of the elastic mesh in allowing error-prone robotic modules to march in formation, surpassing rigidly linked or unlinked modules.
The research carried out by the Sheffield scientists opens up exciting possibilities for the development of ultra-low-power robotic fabrics that can navigate spaces inaccessible to humans. These fabrics could be employed to inspect underground water pipes for cracks or be deployed inside the human body for medical monitoring and treatment.
Prototype fabrics and intelligent Kilobots
The prototype fabrics developed in this study consist of small robotic modules known as Kilobots. Due to their compact size, these Kilobots are characterized by their low power and limited processing capabilities. Each Kilobot uses vibration motors for movement but lacks precise control over its direction. However, when integrated into the elastic mesh, these modules communicate with nearby modules, enabling the group to determine the most effective way to move and behave collectively.
Traditionally, groups of Kilobots and other small modules were not physically linked. However, the Sheffield study demonstrated that coupling these modules via an elastic mesh significantly enhanced their reliability in movement. Dr. Roderich Gross explained that previous studies focused on intelligent fabrics that sense their surroundings or change appearance. At the same time, their research delved into intelligent fabrics that possess the ability to move from one place to another autonomously. These fabrics could effectively navigate spaces inaccessible to humans, such as inspecting the inside of a jet engine.
Applications in medical and industrial fields
Dr. Gross further highlighted the potential of self-moving and stretchable fabrics in medical applications. For instance, these fabrics could wrap around damaged sections of organs, providing high-resolution monitoring or stimulation. Moreover, they could be deployed for industrial purposes, such as inspecting challenging environments or navigating underground pipelines.
Coherent movement enabled by elastic bonds
The study revealed that a fabric comprising more modules achieved more successful and coherent movement. This finding parallels the collective movement observed in bird flocks, known as the many-wrongs principle. Unlike previous research, however, the modules in this study relied not only on information gathering and processing but also on the physical bonds within the elastic mesh. This reduced their dependence on energy-intensive perception and thinking, facilitating the miniaturization and realization of fabrics consisting of thousands of modules.
The study involved researchers from the University of Sheffield, University of Modena and Reggio Emilia, Université Libre de Bruxelles, Santa Catarina State University, and Worcester Polytechnic Institute. The paper titled “Coherent movement of error-prone individuals through mechanical coupling” can be accessed for further details on the research.
The pioneering research conducted by the University of Sheffield scientists has brought us closer to realizing stretchable robotic fabrics. These fabrics, capable of shrinking, growing, and moving with precision, can revolutionize various fields, from industrial inspections to medical interventions, by enabling navigation in inaccessible spaces and providing high-resolution monitoring and treatment options.
Original article and image source: https://www.sheffield.ac.uk/news/
