Revolutionary self-sensing electric artificial muscles

Date:
July 11, 2023
Source:
Queen Mary University of London
Summary:
Researchers have made groundbreaking advancements in bionics with
the development of a new electric variable-stiffness artificial
muscle. This innovative technology possesses self-sensing
capabilities and has the potential to revolutionize soft robotics
and medical applications. The artificial muscle seamlessly
transitions between soft and hard states, while also sensing forces
and deformations. With flexibility and stretchability similar to
natural muscle, it can be integrated into intricate soft robotic
systems and adapt to various shapes. By adjusting voltages,
the muscle rapidly changes its stiffness and can monitor its own
deformation through resistance changes. The fabrication process is
simple and reliable, making it ideal for a range of applications,
including aiding individuals with disabilities or patients in
rehabilitation training.


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FULL STORY ========================================================================== Researchers from Queen Mary University of London have made groundbreaking advancements in bionics with the development of a new electric variable- stiffness artificial muscle. Published in Advanced Intelligent Systems,
this innovative technology possesses self-sensing capabilities and has the potential to revolutionize soft robotics and medical applications. The artificial muscle seamlessly transitions between soft and hard states,
while also sensing forces and deformations. With flexibility and
stretchability similar to natural muscle, it can be integrated into
intricate soft robotic systems and adapt to various shapes. By adjusting voltages, the muscle rapidly changes its stiffness and can monitor its own deformation through resistance changes. The fabrication process is simple
and reliable, making it ideal for a range of applications, including
aiding individuals with disabilities or patients in rehabilitation
training.

In a study published recently in Advanced Intelligent Systems,
researchers from Queen Mary University of London have made significant advancements in the field of bionics with the development of a new
type of electric variable-stiffness artificial muscle that possesses self-sensing capabilities. This innovative technology has the potential
to revolutionize soft robotics and medical applications.

Muscle contraction hardening is not only essential for enhancing strength
but also enables rapid reactions in living organisms. Taking inspiration
from nature, the team of researchers at QMUL's School of Engineering
and Materials Science has successfully created an artificial muscle that seamlessly transitions between soft and hard states while also possessing
the remarkable ability to sense forces and deformations.

Dr. Ketao Zhang, a Lecturer at Queen Mary and the lead researcher,
explains the importance of variable stiffness technology in artificial muscle-like actuators. "Empowering robots, especially those made from
flexible materials, with self-sensing capabilities is a pivotal step
towards true bionic intelligence," says Dr. Zhang.

The cutting-edge artificial muscle developed by the researchers exhibits flexibility and stretchability similar to natural muscle, making it
ideal for integration into intricate soft robotic systems and adapting
to various geometric shapes. With the ability to withstand over 200%
stretch along the length direction, this flexible actuator with a striped structure demonstrates exceptional durability.

By applying different voltages, the artificial muscle can rapidly adjust
its stiffness, achieving continuous modulation with a stiffness change exceeding 30 times. Its voltage-driven nature provides a significant
advantage in terms of response speed over other types of artificial
muscles. Additionally, this novel technology can monitor its deformation through resistance changes, eliminating the need for additional sensor arrangements and simplifying control mechanisms while reducing costs.

The fabrication process for this self-sensing artificial muscle is
simple and reliable. Carbon nanotubes are mixed with liquid silicone
using ultrasonic dispersion technology and coated uniformly using a film applicator to create the thin layered cathode, which also serves as the
sensing part of the artificial muscle. The anode is made directly using
a soft metal mesh cut, and the actuation layer is sandwiched between
the cathode and the anode. After the liquid materials cure, a complete self-sensing variable-stiffness artificial muscle is formed.

The potential applications of this flexible variable stiffness technology
are vast, ranging from soft robotics to medical applications. The
seamless integration with the human body opens up possibilities for
aiding individuals with disabilities or patients in performing essential
daily tasks. By integrating the self-sensing artificial muscle, wearable robotic devices can monitor a patient's activities and provide resistance
by adjusting stiffness levels, facilitating muscle function restoration
during rehabilitation training.

"While there are still challenges to be addressed before these medical
robots can be deployed in clinical settings, this research represents
a crucial stride towards human-machine integration," highlights
Dr. Zhang. "It provides a blueprint for the future development of soft
and wearable robots." The groundbreaking study conducted by researchers
at Queen Mary University of London marks a significant milestone in
the field of bionics. With their development of self-sensing electric artificial muscles, they have paved the way for advancements in soft
robotics and medical applications.

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========================================================================== Journal Reference:
1. Chen Liu, James J. C. Busfield, Ketao Zhang. An Electric
Self‐Sensing and Variable‐Stiffness Artificial Muscle.

Advanced Intelligent Systems, 2023; DOI: 10.1002/aisy.202300131 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2023/07/230711133213.htm

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