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Collaborative robots are expected to physically interact with humans in dailyliving and workplace, including industrial and healthcare settings. A relatedkey enabling technology is tactile sensing, which currently requires addressingthe outstanding scientific challenge to simultaneously detect contact locationand intensity by means of soft conformable artificial skins adapting over largeareas to the complex curved geometries of robot embodiments. In this work, thedevelopment of a large-area sensitive soft skin with a curved geometry ispresented, allowing for robot total-body coverage through modular patches. Thebiomimetic skin consists of a soft polymeric matrix, resembling a humanforearm, embedded with photonic Fiber Bragg Grating (FBG) transducers, whichpartially mimics Ruffini mechanoreceptor functionality with diffuse,overlapping receptive fields. A Convolutional Neural Network deep learningalgorithm and a multigrid Neuron Integration Process were implemented to decodethe FBG sensor outputs for inferring contact force magnitude and localizationthrough the skin surface. Results achieved 35 mN (IQR = 56 mN) and 3.2 mm (IQR= 2.3 mm) median errors, for force and localization predictions, respectively.Demonstrations with an anthropomorphic arm pave the way towards AI-basedintegrated skins enabling safe human-robot cooperation via machineintelligence.

Functional mimicry of Ruffini receptors with Fiber Bragg Gratings and Deep Neural Networks enables a bio-inspired large-area tactile sensitive skin