光纤布拉格光栅
计算机科学
机器人学
触觉传感器
软机器人
算法
光纤
声学
人工智能
物理
电信
机器人
作者
Nikita Shabalov,Alexey A. Wolf,Alexey Kokhanovskiy,A. V. Dostovalov,Sergey A. Babin
标识
DOI:10.1016/j.sna.2024.115219
摘要
Soft 2D tactile sensors are becoming increasingly important in robotics and human-machine interaction. In this paper, we propose a new approach to develop a soft tactile sensor using fiber Bragg gratings (FBGs) and machine learning algorithms. The sensor consists of a layer of silicone elastomer with embedded 192 FBGs that can detect deformations caused by point impact. The FBG responses are then processed by machine learning algorithms to measure the position and the force of impacts with the mean absolute errors of 2.1 mm and 0.34 N, respectively.
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