PHOTOTOUCH: SOFTWARE AND HARDWARE METHODS FOR PHOTOELASTIC TACTILE SENSOR
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Date
2024-04
Authors
Zhuzbay, Nurdaulet
Journal Title
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Volume Title
Publisher
Nazarbayev University School of Engineering and Digital Sciences
Abstract
This thesis introduces a novel approach for predicting force at the fingertips of
tendon driven robotic fingers using the photoelastic effect. The core of this
technique lies in the detection of stress-induced birefringence in silicone, which
becomes visible as distinctive fringe patterns under polarized light. These
patterns emerge when tendons, embedded within a silicone matrix, apply forces
that compress the material. They are not merely visual markers, but also contain
valuable data about the applied forces and their distribution within the silicone.
To extract and utilize this data effectively, Convolutional Neural Network
(CNN) was employed, specially designed to analyze and interpret the intricate
fringe patterns. Thousands of these images were captured in various force
application states, resulting in a substantial dataset for the CNN to learn from.
The finger was used to show the position control and force control capabilities of
photoealastic tactile sensor. It was successful in following the sine wave during
force control mode, with RMSE of 0.59 N at a frequency of 0.05 Hz.
This document will further delve into relevant literature, elaborate on the
research methodology, describe the experimental setup, and present preliminary
findings. Col lectively, these components unveil the immense potential of the
proposed system in augmenting the tactile capabilities of robotic appendages,
with far-reaching implica tions for the fields of robotics and automated systems.
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Type of access: Restricted
Citation
Zhuzbay, N. (2024). Phototouch: Software And Hardware Methods For Photoelastic Tactile Sensor. Nazarbayev University School of Engineering and Digital Sciences