Development of a novel artificial sensitive skin based on different physical transduction technologies of the
tactile physical contact with spike-based neural encoding. The addressed physical transduction technologies will be
capacitive and piezoelectric in particular piezoelectric polymeric films like PVDF-TrFe. We will exploit complementary
features of the two transduction principles i.e. capacitive transducers efficiently measure contact phenomena in the low
frequency range (from DC to up to some tenths of Hz); on the other hand, piezoelectric transducers cover the higher
frequency band (from some Hz up to 1 kHz). The combination of the two can span over the entire frequency range of human
tactile transduction (from DC up to 1 kHz). We will develop spike-based readout based on the neural encoding mechanisms
studied in WP1 and WP2 and design a new spiking skin with interleaved capacitive and piezoelectric sensors. We will
develop circuit architectures to efficiently encode the physical contact information into spike trains of the proper frequency.
We will develop array geometries of the spiking neurons in such a way as to efficiently couple the two transductions.
Effective spike train frequency encoding coupled with smart integration of information from spiking neurons with different
transduction will be developed.
Novel spiking neuron circuit architectures for effectively encode the physical contact information; arrays
of spiking neurons for different body regions (e.g. different geometrical pitch and neuron size). The neural network hardware
will be implemented with dedicated CMOS microelectronics circuits with post-processing steps.
to learn nanotechnologies for tactile sensing
to integrate on-chip SNN for RF
to integrate sensing device on different robotic platform, study additional tactile sensing technology and ft sensors
Enrolments (in Doctoral degree/s)
University of Genova
C. Bartolozzi, M. Valle, R. Dahiya, E. Chicca, S. Terreri