Artificial SA-I and RA-I Afferents for Tactile Sensing of Ridges and Gratings
This work addresses the challenge of improving robot manipulation and prosthetics through biologically-inspired tactile sensing, representing an incremental advance in biomimetic robotics.
The researchers tackled the problem of replicating human tactile sensing in robots by developing biomimetic artificial afferents that mimic natural mechanoreceptors, achieving a match between artificial and natural afferent responses in sensitivity to edges and gaps, and matching human and robot psychometric functions for grating orientation.
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.