Abstract
The ongoing research on and development of increasingly intelligent artificial systems propels the need for bio inspired pressure sensitive spiking circuits. Here we present an adapting and spiking tactile sensor, based on a neuronal model and a piezoelectric field-effect transistor (PiezoFET). The piezoelectric sensor device consists of a metal-oxide semiconductor field-effect transistor comprising a piezoelectric aluminium-scandium-nitride (AlxSc1−xN) layer inside of the gate stack. The so augmented device is sensitive to mechanical stress. In combination with an analogue circuit, this sensor unit is capable of encoding the mechanical quantity into a series of spikes with an ongoing adaptation of the output frequency. This allows for a broad application in the context of robotic and neuromorphic systems, since it enables said systems to receive information from the surrounding environment and provide encoded spike trains for neuromorphic hardware. We present numerical and experimental results on this spiking and adapting tactile sensor.
Highlights
The ongoing research on and development of increasingly intelligent artificial systems propels the need for bio inspired pressure sensitive spiking circuits
Besides the adaptation of sensory neurons to a constant stimulus, spike-frequency adaptation is present in neurons even far from sensory systems and can rise not just through c ellular[11,12], and network induced m echanisms[13,14]. These biological findings served as a guideline to develop a tactile sensor based on piezoelectric A lxSc1−xN (AlScN) within the fields of neuromorphic engineering and robotics
This fundamental working principle is the same for the piezoelectric oxide semiconductor field effect transistor (POSFET) and PiezoFET, we would like to emphasise that the here presented PiezoFET based on AlScN exhibits a few distinguishing features
Summary
The ongoing research on and development of increasingly intelligent artificial systems propels the need for bio inspired pressure sensitive spiking circuits. Besides the adaptation of sensory neurons to a constant stimulus, spike-frequency adaptation is present in neurons even far from sensory systems and can rise not just through c ellular[11,12], and network induced m echanisms[13,14] These biological findings served as a guideline to develop a tactile sensor based on piezoelectric A lxSc1−xN (AlScN) within the fields of neuromorphic engineering and robotics. Besides the development of single sensor devices for the conversion of stress into an electrical quantity, a tremendous progress regarding analogue circuit design was made over the last decades[42] This ranges from the development of biologically inspired circuits like the adaptive exponential I&F neuron[43,44] and their integration in spiking deep neural networks[45] to mixed signal circuits which exploit events for processing visual information[46,47,48,49]. Experimental findings performed with the touch sensor to demonstrate the spike coding of the applied forces as well as the exponential adaptation of the system are presented
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