TY - JOUR

T1 - Soft 2D tactile sensor based on fiber Bragg gratings and machine learning algorithms

AU - Shabalov, N.

AU - Wolf, A.

AU - Kokhanovskiy, A.

AU - Dostovalov, A.

AU - Babin, S.

N1 - Russian Science Foundation (21-72-30024). The work of AK was financially supported by ITMO Fellowship Program.

PY - 2024/4/16

Y1 - 2024/4/16

N2 - 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.

AB - 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.

KW - Fiber Bragg grating

KW - Machine learning algorithms

KW - Soft tactile sensors

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85186371042&origin=inward&txGid=54d85caa11e4357a12498c77947f4219

UR - https://www.mendeley.com/catalogue/e178f552-d4d8-3831-9e65-eaec2e636fe3/

U2 - 10.1016/j.sna.2024.115219

DO - 10.1016/j.sna.2024.115219

M3 - Article

VL - 369

JO - Sensors and Actuators, A: Physical

JF - Sensors and Actuators, A: Physical

SN - 0924-4247

M1 - 115219

ER -