Gradient-interlayer-based flexible pressure sensors for high-performance robotic perception

Tactile perception systems based on flexible pressure sensors are indispensable for humanoid robots to perform dexterous manipulation, compliant interaction, and operation in visually challenging environments. Although strategies relying on surface or spatial microstructure engineering have improved sensor performance, the long-standing trade-off among sensitivity, sensing range, and linearity continues to hinder their practical deployment. Inspired by the gradient distribution of mechanoreceptors in human fingertip skin, we report a gradient-interlayer-based flexible iontronic pressure sensor (GriFIPS) in which a single direct-ink-written elastomeric mesh-like interlayer, with a centrifugal increase in aperture size, is placed between the soft electrode and an ionic hydrogel layer. Operating upstream of the functional layer, the mesh enables progressive, stage-wise contact under increasing load and decouples macroscopic contact-area evolution from the microscopic interfacial response. The sensor simultaneously achieves a sensitivity of 175.9 kPa^-1, a linear sensing range up to 360 kPa with a coefficient of determination of 0.997, a low detection limit of about 2.1 Pa, and a response time of about 25 ms, while remaining stable over 6000 loading cycles and 2000 cycles of 50% tensile strain. Building on this single-channel device, we further extend the architecture into a 3-axis gradient-interlayer-based flexible iontronic force sensor (3-axis GriFIFS) capable of resolving triaxial forces and surface textures. When integrated onto a dexterous robotic hand and combined with a temporal convolutional network, the sensors support tactile object recognition, fabric texture discrimination, human-robot interaction, and tactile-guided assembly, offering a generalizable route to tactile sensing for embodied intelligence.