Development of Soft Tactile Sensor for Force Measurement and Position Detection

TL;DR

This paper presents a novel soft tactile sensor inspired by human skin that can simultaneously measure contact force and location, using a dual-layer structure with signal processing and machine learning for accurate, robust detection in contact-rich robotic tasks.

Contribution

A new dual-layer soft tactile sensor design capable of simultaneous force and position detection, with integrated signal processing and machine learning for improved accuracy.

Findings

High accuracy in force measurement demonstrated

Reliable contact location detection achieved

Sensor robustness validated through experiments

Abstract

As more robots are implemented for contact-rich tasks, tactile sensors are in increasing demand. For many circumstances, the contact is required to be compliant, and soft sensors are in need. This paper introduces a novelly designed soft sensor that can simultaneously estimate the contact force and contact location. Inspired by humans' skin, which contains multi-layers of receptors, the designed tactile sensor has a dual-layer structure. The first layer is made of a conductive fabric that is responsible for sensing the contact force. The second layer is composed of four small conductive rubbers that can detect the contact location. Signals from the two layers are firstly processed by Wheatstone bridges and amplifier circuits so that the measurement noises are eliminated, and the sensitivity is improved. An Arduino chip is used for processing the signal and analyzing the data. The contact force can be obtained by a pre-trained model that maps from the voltage to force, and the contact location is estimated by the voltage signal from the conductive rubbers in the second layer. In addition, filtering methods are applied to eliminate the estimation noise. Finally, experiments are provided to show the accuracy and robustness of the sensor.