Soft 2D tactile sensor based on fiber Bragg gratings and machine learning algorithms

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. [Display omitted] •2D flexible tactile sensor with array of 192 FBG sensors was shown.•Experimental calibration of 2D tactile sensors with assistance of machine learning algorithm was presented.•Prediction of pressing force with mean absolute error of 0.34 N was demonstrated.•Prediction of position of the impact with mean absolute error of 2.1 mm was achieved.