posted on 2020-03-18, 12:04authored bySaeb Mousavi, David Howard, Fenghua Zhang, Jinsong Leng, Chun H. Wang
A key
missing technology for the emerging field of soft robotics is the
provision of highly selective multidirectional tactile sensing that
can be easily integrated into a robot using simple fabrication techniques.
Conventional strain sensors, such as strain gauges, are typically
designed to respond to strain in a single direction and are mounted
on the external surface of a structure. Herein, we present a technique
for three-dimensional (3D) printing of multidirectional, anisotropic,
and constriction-resistive strain sensors, which can be directly integrated
into the interior of soft robots. Using a carbon-nanotube-reinforced
polylactic acid (PLA-CNT), both the sensing element and the conductive
interconnect of the sensor system are 3D-printed. The sensor’s
sensitivity and anisotropy can be adjusted by controlling the air
gap between printed adjacent tracks, infill density, and build orientation
relative to the main loading direction. In particular, sensors printed
with a near-zero air gap, i.e., adjacent tracks forming a kissing
bond, can achieve a gauge factor of ∼1342 perpendicular to
the raster orientation and a gauge factor of ∼1 parallel to
the raster orientation. The maximum directional selectivity of this
ultrasensitive sensor is 31.4, which is approximately 9 times greater
than the highest value reported for multidirectional sensors so far.
The high sensitivity stems from the progressive opening and closing
of the kissing bond between adjacent tracks. The potential of this
type of sensors and the simple manufacturing process are demonstrated
by integrating the sensor with a soft robotic actuator. The sensors
are able to identify and quantify the bending deformation and angle
in different directions. The ability to fabricate sensors with tailored
footprints and directional selectivity during 3D printing of soft
robotic systems paves the way toward highly customizable, highly integrated
multifunctional soft robots that are better able to sense both themselves
and their environments.