A group of Italian researchers has developed a 3D-printed artificial skin that could be used to improve robots’ tactile sensing capabilities.
Researchers of Scuola Superiore Sant’Anna† Ca’ Foscari University of Veniceand the Sapienza University of Rome created the 3D-printed skin that successfully mimicked the function of Ruffini receptors, a type of cell on subcutaneous human skin tissue that senses stretching, vibration, heat and pressure.
Once attached to a robot and combined with a deep learning algorithm based on a multi-layered convolutional neural network (CNN), the skin can estimate the force and point at which the robot comes into contact with an object, potentially making a safer human. robot enables collaboration in the future.
3D printing artificial skin
3D bioprinted skin models and grafts have received increasing interest and development in recent years due to their potential applications for: disease modeling† testing the efficacy of new treatmentsand providing a alternative to animal testing†
Bioprinted skin has also received attention for its potential for more effective wound healing treatments, such as the NOVOLASM cold plasma technology from the consortium for: treating infected burns and skin graftsand the University of Birmingham and University of Huddersfield’s SLAM 3D bioprinting technique to treat chronic skin wounds†
3D-printed skin is being tested even as far away as space, with astronauts on the International Space Station (ISS) develop bioprinted dressings made from their own cells that could be used to better heal flesh wounds in space.
Improving robotic tactile sensing
However, the Italian research group is investigating bioprinted artificial skin for a different purpose; improving the tactile sensing capabilities of robots. In particular, the study’s findings could potentially improve the performance of mobile robots that interact with humans in a range of real-world environments, such as public spaces, home environments, healthcare facilities and offices.
By replicating humans’ biological sensory processes on existing and future robots, the researchers hope to improve the performance of mobile robots for a range of interactive and manual tasks and reduce safety risks when used alongside human workers in industrial settings.
To achieve this, the team focused on replicating the function of Ruffini receptors, small and slowly adapting cells that detect interactions between the skin and external objects and stimuli, such as heat, pressure and contact.
The researchers 3D bioprint an 8 mm thick soft, curved and stretchable polymer layer integrated with a 430 mm long optical fiber. The biomimetic ‘skin’ resembled a piece of human forearm, while the optical fiber contained Bragg transducers (FBG) made of photonic fibers that could mimic the functionality of Ruffini receptors.
The skin was then applied to the robot to enable it to detect stimuli in its environment.
To decode the FBG sensor outputs, the team developed a CNN-based deep learning algorithm and a multi-grid neuron integration process that informed the robot about the power and point of contact of external stimuli. The researchers then tested their bioprinted skin and algorithm through a series of simulations, in which it reportedly achieved “very promising results” in predicting the force applied to the robot and where it was applied.
In the paper, the researchers say their findings could pave the way for AI-integrated artificial skins that will enable safer human-robot collaboration in the future. In the future, the team says their bioprinted skin can be implemented on a variety of humanoid robots, as the modular skin patches can be linked together to match different robot architectures and shapes.
Therefore, the next step in the researchers’ research is to investigate to what extent their bioprinted skin can be applied to other robotic systems.
More information about the research can be found in the article titled: “Functional mimicry of Ruffini receptors with Bragg fiber lattices and deep neural networks enables bio-inspired, large-area tactile sensitive skin”, published in the journal Nature Machine Intelligence. The study is co-authored by L. Massari, G. Fransvea, J. D’Abbraccio, M. Filosa, G. Terruso, A. Aliperta, G. D’Alesio, M. Zaltieri, E. Schena, E. Palermo , E. Sinibaldi and C. Oddo.
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Featured image shows the 3D printed artificial skin. Image via Nature Machine Intelligence.