Double-layer staggered IWFBGs enable multi-dimensional tactile sensing on scalable flexible skin

Flexible tactile skins with dense, multimodal sensing are important for dexterous robots and wearable human-machine interfaces, yet electrical and magnetic sensors often suffer from electromagnetic interference and complex wiring, while existing optical designs have limited functionality or scalability. We present a flexible tactile skin based on double-layer staggered identical weak fiber Bragg gratings (IWFBGs) interrogated by optical frequency-domain reflectometry (OFDR) for simultaneous sensing of contact location, normal force, and contact orientation. A simulation-driven design framework combining finite element analysis and neural networks is used to compare four IWFBG layouts and identify the double-layer staggered architecture as optimal. To suppress temperature drift and laser instability, we further introduce a MAD-assisted moving-average detrending algorithm that improves the linearity of wavelength-force responses. Subsequently, this study implemented tactile information prediction on a 70 mm × 70 mm sensor using a backpropagation (BP) neural network. In terms of localization, a root mean square error of 3.2-3.5 mm was achieved, while force sensing attained a mean absolute error of 0.27 N. Directional accuracy across four contact directions reached 88%. Furthermore, by further testing the predictive performance of the BP algorithm on unseen locations of the sensor, it is demonstrated that the system possesses spatially continuous resolution capability, highlighting its potential for optical tactile skin applications.