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.

中文翻译：

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基于光纤布拉格光栅和机器学习算法的软 2D 触觉传感器

软 2D 触觉传感器在机器人和人机交互中变得越来越重要。在本文中，我们提出了一种使用光纤布拉格光栅（FBG）和机器学习算法开发软触觉传感器的新方法。该传感器由一层硅胶弹性体组成，内嵌 192 个 FBG，可以检测点冲击引起的变形。然后，FBG 响应通过机器学习算法进行处理，以测量冲击位置和冲击力，平均绝对误差分别为 2.1 毫米和 0.34 N。