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Scientific Reports on Micro and Nanosystems
edited by Christofer Hierold
Vol. 36
Johannes Weichart
Artificial Fingertip
with Embedded
High Resolution
Tactile Sensing
1st Edition 2023. (10), XX, 158 pages. 64,00.
ISBN 978-3-86628-802-7
Abstract
The
replication of the human sense of touch in robots or prostheses would greatly
enhance their ability to interact with the environment. This thesis
investigates the possibility to rebuild a human fingertip with its mechanical
sensing capabilities. A soft, human-sized artificial fingertip was developed,
equipped with an array of 144 tactile sensors (taxels).
These 0.5 mm diameter taxels can detect touch,
vibrations, and shear, enabling the artificial finger to distinguish between
different external stimuli.
This thesis
describes the design of the taxels, the fabrication
as well as the characterization. The taxels can sense
pressures with a sensitivity of 2.6 kPa−1 and were tested in a
temperature range of 20 - 80° C as well as over 10'000 cycles. The sensing
characteristics are determined by the thickness of a spray-coated silicone
layer that encases the sensors, increasing their robustness to external
influences. The static and dynamic sensing capabilities of the encapsulated taxels were evaluated. The sensitivity can be modifed according to the needs of an application. Skin
thicknesses between 0 - 660µm allowed sensitivities of 0.86 - 0.035
kPa−1. A similar trend was observed for dynamic sensing capabilities.
The softness
of a human finger was measured to create an artificial finger of similar
conformity. Simulation results supported the transfer of taxel
characteristics from on-chip to the soft fingertip. Miniaturized readout
electronics allowed to read the full finger at 220 Hz,
enabling the observation of touch and slipping events on the artificial finger
and the estimation of the contact force. Slipping events can be detected as
vibrations registered by individual sensors, while the contact force can be
estimated by averaging sensor array readouts. The robustness of the fingers was
tested by applying 15 N for >2000 times, which resulted in only minor
degradation in stiffened membranes. Neural networks were tested to extract
simple features like object recognition or the evaluation of contact force and
location. Good classification scores of ∼90% could be achieved on an early
version of the artificial finger.
Keywords: human sense of touch, robots, prostheses, artificial
finger, taxels
Scientific Reports on Micro and Nanosystems
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