Design, Motivation and Evaluation of a Full-Resolution Optical Tactile Sensor

Sensors
Carmelo Sferrazza, Raffaello D'Andrea

Abstract

Human skin is capable of sensing various types of forces with high resolution and accuracy. The development of an artificial sense of touch needs to address these properties, while retaining scalability to large surfaces with arbitrary shapes. The vision-based tactile sensor proposed in this article exploits the extremely high resolution of modern image sensors to reconstruct the normal force distribution applied to a soft material, whose deformation is observed on the camera images. By embedding a random pattern within the material, the full resolution of the camera can be exploited. The design and the motivation of the proposed approach are discussed with respect to a simplified elasticity model. An artificial deep neural network is trained on experimental data to perform the tactile sensing task with high accuracy for a specific indenter, and with a spatial resolution and a sensing range comparable to the human fingertip.

References

Jan 1, 1984·Experimental Brain Research·G Westling, R S Johansson
Feb 5, 2005·IEEE Computer Graphics and Applications·Kazuto KamiyamaSusumu Tachi
May 24, 2007·The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS·J Dargahi, S Najarian

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Citations

Sep 25, 2019·Sensors·Kazuhiro Shimonomura
Aug 14, 2020·Sensors·Fariborz Baghaei NaeiniYahya Zweiri
Mar 16, 2021·Frontiers in Robotics and AI·Matthias HoferRaffaello D'Andrea

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Methods Mentioned

BETA
force measurements

Software Mentioned

RMSProp

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