Science & Technology, UK (Commonwealth Union) – Recent research conducted by scientists at the University of Sheffield has brought us closer to the realization of robotic fabrics capable of undergoing size adjustments and intricate movements with precision. Spearheaded by Dr. Roderich Gross of the University’s Department of Automatic Control and Systems Engineering, this study has unveiled a groundbreaking achievement: the successful interconnection of diminutive, energy-efficient robotic modules, each about the size of a 50p coin, through an adaptable elastic mesh. This mesh facilitates coordinated movement in a consistent direction, resulting in the creation of an intelligent robotic fabric.
Published in the journal Nature Communications, this research marks the pioneer instance where supple connections empower these robotic modules to move synchronously in a formation, surpassing the performance of rigidly linked or unlinked counterparts.
The implications of this work are far-reaching. It charts a course for the future development of ultra-low-power robotic fabrics tailored to traverse spaces beyond human reach. These fabrics could venture into confined spaces like subterranean water pipes, systematically inspecting for structural flaws. Moreover, they could potentially shrink in size and be deployed within the human body for medical monitoring or treatment applications.
In this study, the prototype fabrics take shape through the integration of small robotic modules known as Kilobots. These Kilobots possess limited computational capabilities and operate on low power, attributed to their compact size. Employing vibration motors for locomotion, individual Kilobots lack precise self-direction control. However, once integrated into the elastic mesh, they establish communication with nearby modules, collectively determining optimal movement patterns and behavior.
Traditionally, groups of Kilobots and other diminutive modules remain physically independent. Nevertheless, the Sheffield study exemplifies how uniting these modules within an adaptable elastic mesh greatly enhances their reliability in movement.
Dr Roderich Gross, who is a Senior Lecturer in Robotics and Computational Intelligence, from the University of Sheffield, says “Previous studies have looked at intelligent fabrics that sense their surroundings or change appearance. This study looks at intelligent fabrics that move from one place to another, meaning they could deploy themselves without human assistance. In the future, such fabrics could effectively navigate spaces inaccessible to humans, for example, for inspecting the inside of a jet engine.”
“In the long term, self-moving, stretchable fabrics may be deployed in medical applications, for example, wrapping around a damaged section of an organ and then monitoring or stimulating it at high spatial resolution.”
The research involved the creation of robotic fabrics containing 49 Kilobot modules. The results of their experiments revealed that a single module lacked the ability to move independently in a straight line. A fabric composed of 16 modules could manage a brief straight-line movement, but only for a limited time. Notably, as the fabric incorporated more modules, its success in maintaining a unified direction of movement increased.
Additional experiments showcased the fabric’s capacity to maneuver successfully along specific paths, including a circular trajectory. The fabric also demonstrated an intriguing ability to reshape itself to fit through hypothetical confined spaces, subsequently returning to its original form. Conversely, when the modules were assembled into a rigid mesh, their capability to move cohesively in a desired direction was compromised.
Analogous to the coordinated flight of birds in flocks, the study underscored that a larger assembly of individuals was more adept at collaboratively determining movement, in contrast to a smaller group. In a departure from prior investigations into the many-wrongs principle, the modules examined by the scholars from Sheffield University exhibit a distinctive approach. Unlike the exclusive dependence on information gathering and utilization seen in earlier studies, these modules find support in the tangible connections woven within the elastic mesh. As a result, the negotiation process is less reliant on energy-intensive perception and cognitive processing for achieving harmonious actions. This novel approach holds the potential to facilitate the miniaturization of these modules and advance the concept of fabric incorporating a multitude of thousands of such modules.
