FPGA implementation of a FA-1 mechanoreceptor model for efficient representation of tactile features

Abstract

Spatiotemporal spike patterns from a population of mechanoreceptors provide a concise representation of tactile stimuli that facilitates rapid sensory processing in the brain. Efficient models of mechanoreceptors are needed for the adoption of spike-based processing for robotic tactile sensing applications. This paper presents a biomimetic model of the fast-adapting type 1 (FA-1) mechanoreceptor, implemented on a field-programmable-gate-array (FPGA). The simplicity of this model enables its realization on large arrays of sensing elements while operating with sub-millisecond temporal precision required to capture deformation patterns. We illustrate this capability by interfacing with a 4096 element tactile sensor array with a 5.2 kHz sampling rate. Through physical experiments, we demonstrate the discrimination of force magnitude and local curvature during transient mechanical contact, using spike patterns obtained from the model. The approach has the potential to deliver responsive full-body tactile sensing in robotic and prosthetic applications.