Adaptive SNN for Anthropomorphic Finger Control.

Mircea Hulea,George Iulian Uleru,Constantin Florin Caruntu

doi:10.3390/s21082730

Mircea Hulea, George Iulian Uleru + Show 1 more

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https://doi.org/10.3390/s21082730

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Abstract

Anthropomorphic hands that mimic the smoothness of human hand motions should be controlled by artificial units of high biological plausibility. Adaptability is among the characteristics of such control units, which provides the anthropomorphic hand with the ability to learn motions. This paper presents a simple structure of an adaptive spiking neural network implemented in analogue hardware that can be trained using Hebbian learning mechanisms to rotate the metacarpophalangeal joint of a robotic finger towards targeted angle intervals. Being bioinspired, the spiking neural network drives actuators made of shape memory alloy and receives feedback from neuromorphic sensors that convert the joint rotation angle and compression force into the spiking frequency. The adaptive SNN activates independent neural paths that correspond to angle intervals and learns in which of these intervals the rotation the finger rotation is stopped by an external force. Learning occurs when angle-specific neural paths are stimulated concurrently with the supraliminar stimulus that activates all the neurons that inhibit the SNN output stopping the finger. The results showed that after learning, the finger stopped in the angle interval in which the angle-specific neural path was active, without the activation of the supraliminar stimulus. The proposed concept can be used to implement control units for anthropomorphic robots that are able to learn motions unsupervised, based on principles of high biological plausibility.

Highlights

In the biological world, information is processed using impulses or spikes that provide living creatures with the ability to be aware of the surrounding environment and to act
The experiments demonstrate that a bioinspired control system based on an adaptive neural structure of biological inspiration and contractile shape memory alloy (SMA) actuators is sensitive to the rotation angle of an anthropomorphic finger
This is achieved by the activation of different neural paths for different values of the input potential that correspond to several angle intervals

Summary

Introduction

Information is processed using impulses or spikes that provide living creatures with the ability to be aware of the surrounding environment and to act . Considering that the frequency generated by the spindles increases with the muscle stretch by an external force [4], the spindle output can be used to determine the rotation angle of articulation. This function cannot be applied when the muscle contracts, because the spindle response to acceleration dominates their response during a passive stretch [5]. The Golgi organs respond to the force applied to the tendons, providing information about the muscle activity [6].

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