Abstract
The need to develop electronic skin (e-skin) for robotics is essential to provide a sense of touch on a large area, the same as human skin. This paper reports the design and development of printed e-skin force sensor arrays. The performance analysis of these capacitive force sensor arrays showed a resolution of 2.5 sq. mm, localization accuracy of 99% and a sensitivity of 0.53 pF/N. The sensor patches provided significant force sensitivity and stable loading and unloading for static force. A graphical user interface is developed in open-source python software. An unsupervised machine learning algorithm trains the tactile e-skin system for different user styles to distinguish the cluster of lower and higher touch angles for improving accuracy. The proposed e-skin sensor finds application in large-area sensors and gripper pads for prosthetics in biomedical devices where the sense of touch and high resolution is needed.
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