ML-based tactile sensor calibration: A universal approach
Robotics
2016-06-22 v1 Machine Learning
Abstract
We study the responses of two tactile sensors, the fingertip sensor from the iCub and the BioTac under different external stimuli. The question of interest is to which degree both sensors i) allow the estimation of force exerted on the sensor and ii) enable the recognition of differing degrees of curvature. Making use of a force controlled linear motor affecting the tactile sensors we acquire several high-quality data sets allowing the study of both sensors under exactly the same conditions. We also examined the structure of the representation of tactile stimuli in the recorded tactile sensor data using t-SNE embeddings. The experiments show that both the iCub and the BioTac excel in different settings.
Keywords
Cite
@article{arxiv.1606.06588,
title = {ML-based tactile sensor calibration: A universal approach},
author = {Maximilian Karl and Artur Lohrer and Dhananjay Shah and Frederik Diehl and Max Fiedler and Saahil Ognawala and Justin Bayer and Patrick van der Smagt},
journal= {arXiv preprint arXiv:1606.06588},
year = {2016}
}