Tactile-Sensor Embedded Robotic Skins for Fine-Grained Dexterity

Abstract

The integration of tactile sensors into robotic skins represents a transformative milestone in the advancement of dexterous robotic manipulation. Over the past decade, the convergence of flexible electronics, microfabrication techniques, and soft-material engineering has enabled the development of tactile-sensor embedded skins that closely mimic the human sense of touch. These skins incorporate dense arrays of taxels—individual tactile sensing units— that can detect normal forces, shear forces, and even subtle texture variations. By distributing these sensing elements beneath compliant elastomeric layers, robotic systems gain the ability to perform adaptive grasping, prevent object slippage, and interact safely with delicate or unpredictable environments. In this work, we present a comprehensive framework for the design, fabrication, calibration, and evaluation of a multi-modal robotic skin featuring both capacitive and optical sensing modalities. We detail the materials selection process, manufacturing steps, electronics integration, and data acquisition architecture. Calibration protocols establish the relationships between applied forces and sensor outputs, ensuring accuracy across a broad dynamic range. Experimental evaluations demonstrate sub-gram force resolution, spatial discrimination below half a millimeter, and reliable texture classification with over 95% accuracy. Durability testing confirms sustained performance after extensive mechanical cycling. We conclude by discussing how tactile feedback enhances closed-loop control in manipulation tasks, outlining current limitations— such as power consumption and data bandwidth—and proposing future research directions, including on-skin preprocessing, machine-learning–driven perception, and large-area scalable fabrication.