  For robot touch to converge with the human sense of touch, artificial
transduction should involve biologically-plausible population codes analogous
to those of natural afferents. Using a biomimetic tactile sensor with
3d-printed skin based on the dermal-epidermal boundary, we propose two novel
feature sets to mimic slowly-adapting and rapidly-adapting type-I tactile
mechanoreceptor function. Their plausibility is tested with three classic
experiments from the study of natural touch: impingement on a flat plate to
probe adaptation and spatial modulation; stimulation by spatially-complex
ridged stimuli to probe single afferent responses; and perception of grating
orientation to probe the population response. Our results show a match between
artificial and natural afferent responses in their sensitivity to edges and
gaps; likewise, the human and robot psychometric functions match for grating
orientation. These findings could benefit robot manipulation, prosthetics and
the neurophysiology of touch.
