An Automated Tactile Stimulator Apparatus for Neuromorphic Tactile Sensing

Abstract

Tactile sensing is an active area of research in robotics and neural engineering, particularly in relation to sensory feedback for neural prostheses. Sensory feedback relies on neuromorphic models for touch, which must be characterized and validated through tactile sensing experiments. Currently, no standardized, automated method exists for performing these experiments. Thus, there exists a need for new methods/workflows for providing tactile stimulation in neuromorphic tactile sensing. In this work, we describe a rotary-drum tactile stimulator that provides complete user control over force and velocity setpoints and applied textures using PID tuning and an interchangeable, snap-in 3D-printed texture plate system. We achieve high accuracy and precision closed-loop force control (3.4% average deviation in force between first and last ten trials with 4.2% standard deviation) and open-loop velocity control (4.6% average deviation from velocity setpoint with 2.6% standard deviation). Additionally, the apparatus features an automated data pipeline, which records analog tactile sensor readings at each experimental condition, automatically segments them into individual palpation trials, and transforms them into neuromorphic spiking activity. Though designed to develop neuromorphic models of touch for prostheses, the apparatus is generalizable to a wide array of neural engineering experiments, including characterizing tactile sensors and generating tactile sensing databases.