We describe experiments aimed at assessing the applicability of fibre Bragg grating sensors to distributive tactile
sensing. Strain signals from flexible surfaces instrumented with Bragg grating sensors are processed using neural
networks so as to obtain the location, shape and orientation of objects placed on the surfaces.
Tactile sensors are needed for many emerging robotic and telepresence
applications such as keyhole surgery and robot operation in
We have proposed and demonstrated a tactile sensor consisting of a
fibre Bragg grating embedded in a polymer "finger". When the sensor
is placed in contact with a surface and translated tangentially across
it measurements on the changes in the reflectivity spectrum of the
grating provide a measurement of the spatial distribution of forces
perpendicular to the surface and thus, through the elasticity of the
polymer material, to the surface roughness.
Using a sensor fabricated from a Poly Siloxane polymer (Methyl Vinyl
Silicone rubber) spherical cap 50 mm in diameter, 6 mm deep with an
embedded 10 mm long Bragg grating we have characterised the first and
second moment of the grating spectral response when scanned across
triangular and semicircular periodic structures both with a modulation
depth of 1 mm and a period of 2 mm. The results clearly distinguish
the periodicity of the surface structure and the differences between
the two different surface profiles. For the triangular structure a
central wavelength modulation of 4 pm is observed and includes a
fourth harmonic component, the spectral width is modulated by 25 pm.
Although crude in comparison to human senses these results clearly
shown the potential of such a sensor for tactile imaging and we expect
that with further development in optimising both the grating and
polymer "finger" properties a much increased sensitivity and spatial
resolution is achievable.
Two distributive tactile sensing systems are presented, based on fibre Bragg grating sensors. The first is a onedimensional metal strip with an array of 4 sensors, which is capable of detecting the magnitude and position of a contacting load. This system is compared experimentally with a similar system using resistive strain gauges. The second is a two-dimensional steel plate with 9 sensors which is able to distinguish the position and shape of a contacting load. This system is compared with a similar system using 16 infrared displacement sensors. Each system uses neural networks to process the sensor data to give information concerning the type of contact.