by Ingrid Fadelli , Tech Xplore
During damage detection trials, the researchers’ hydrogel-based skin became injured. Hardman, Thuruthel, and Iida deserve credit.
Roboticists have been working for decades to create robots that, in terms of appearance and functionality, are quite similar to humans. Recent breakthroughs in technology, like as the introduction of more sophisticated sensors and pliable artificial skins, have created exciting new avenues for the development of robotic systems that resemble humans.
A novel hydrogel-based skin was recently developed by researchers at the University of Cambridge’s Bio-Inspired Robotics Lab. This skin could enable robots to mimic human touch perception by detecting an object’s tactile characteristics. This extremely flexible skin, which was described in a work that was published in Materials Today Electronics, uses a model-free computational technique together with a series of electrodes to reconstruct tactile stimuli.
One of the researchers who conducted the study, David Hardman, told TechXplore that “researchers all over the world have been interested in how robots can be manufactured from flexible and stretchable materials recently.” “These’soft’ robots can perform jobs that are extremely challenging for typical ‘rigid’ robots, and they are safer to work with because they don’t damage the objects they interact with. But in order to fully benefit, every part of a robot—including its sensors—must be soft.”
Hardman and his colleagues set out to design a stretchable sensing material that could sense objects or human touch, monitor its surrounding environment, and identify damage—all while taking inspiration from human skin. Their synthetic skin is built upon a hydrogel, which is a material that is insoluble in water and contains water inside it) coupled with an electrode-based hardware system.
“We use a specially developed sensorized hydrogel as the basis of our skin, since this is biodegradable, customizable, and very stretchable,” said Hardman. “We combine this with Electrical Impedance Tomography (EIT) equipment, which applies currents and measures voltages using electrodes at the skin’s edge to provide information about the condition of the skin. We attempt to determine whether the skin has been harmed or where it has been touched by using these voltages.”
The experimental setup of the team. A robotic arm was used to probe a sensorized hydrogel skin, and electrodes placed around the skin’s edge were used to gather a range of measurements. Hardman, Thuruthel, and Iida deserve credit.
Using a modest quantity of real-world data, Hardman and colleagues developed deformation maps for their hydrogel-based system, as opposed to most existing artificial skins that analyze the data gathered by electrodes using a typical neural network-based architecture. Their method achieved an average resolution of 12.1 mm over a 170 mm circular skin in initial evaluations, greatly outperforming an artificial skin system based on traditional neural networks.
“Combining electrical impedance tomography technologies with functional sensorised skins results in a set of problems which are very hard to solve using purely mathematical approaches,” stated Hardman. We’ve shown how to significantly simplify this by incorporating a tiny bit of actual data from the real world into our computations. As a result, we can now begin to address applications that would be unimaginable with an analytical approach by covering our robots’ whole surface in soft touch sensors.”
To date, Hardman and associates have evaluated the feasibility of their hydrogel-based skin for three major practical uses: damage localization or detection, environmental monitoring, and recognition of various tactile inputs. All three of these tasks were completed successfully by their system, indicating that it could be employed to enhance the capabilities of soft robotic systems designed to tackle different missions.
“We are currently working on improving the shape and size of the skins so that they can be used to sense much more complex stimuli,” said Hardman. “For example, if the skin were applied onto a robotic hand we would like it to sense not only the location and force of touches to the skin, but also the position of each finger and whether the hand has been damaged.”