New intrinsically stretchable electronic skin (“e-skin”) based proprioception system capable of providing accurate, high-resolution, real-time and full-geometry characterization of a soft object’s shape and position.
This technology allows the determination of a soft object’s movement, action, and location, enabling the precise control, operability, and practical implementation of soft robots and other soft systems.
Soft devices, and in particular soft robots, offer ground-breaking
approaches to address technological challenges for which conventional
rigid systems are simply unfit. These include surgical robotics,
compliant prostheses, industrial processes and wearable technologies.
Soft systems offer intrinsically safer and more life-like interactions, however, their conformable structure also makes their characterization difficult and limits the determination of an object’s movement, action and location (so-called 3-dimensional proprioception) which is essential for controllability and operability required for the practical implementation of such innovations.
To overcome this, University of Edinburgh researchers have developed a new 3D-proprioception system that enables real-time, high-accuracy three-dimensional, full-geometry shape reconstruction suitable for use with soft robots and other soft systems.
The Edinburgh technology is underpinned by a new capacitive ‘e-skin’ design in combination with an innovative deep learning methodology. Our solution provides real-time (30 fps), high accuracy (mm-scale error), full-geometry shape reconstruction of dense point clouds of 3D-geometries under complex multimodal deformations (i.e. bending, twisting, elongation and their combinations). This represents a major advancement over existing approaches for soft robot proprioception that is limited to sparse geometrical inference under one or two prescribed types of deformations.
The Edinburgh e-skin technology is intrinsically stretchable,
scalable and can be deployed either as an integral component of a
product or as an external layer applied to the surface of the object.
With a rapid training pipeline that is agnostic of the soft object’s
shape, size and geometry, the technology can be readily deployed with
any soft device where 3D-proprioception is desirable.
Yang et al, Smart capacitive e-skin takes soft robots beyond proprioception, pre-print available at: https://www.researchsquare.com/article/rs-1501113/v1