Self‐Assembled Magnetic Cilia Skin for Five‐Degree‐of‐Freedom Tactile Sensing via Hybrid Physics–Neural Decoding

Advanced tactile skin technologies capable of simultaneously measuring contact location and multiaxis forces are essential for next‐generation human–robot interaction and dexterous manipulation. However, existing sensors remain limited in simultaneously resolving multidimensional signals under combined loading. Here, we present a self‐assembled magnetic cilia‐based soft skin sensor with a hybrid decoding pipeline for real‐time five‐degree‐of‐freedom (5‐DoF) tactile estimation. A magnetic field‐induced self‐assembly process yields high‐aspect‐ratio cilia arrays without lithographic patterning, achieving a signal‐to‐noise ratio (SNR) improvement of approximately 24 dB over planar magnetic films. A hybrid decoding pipeline that combines a convolutional neural network (CNN) with a calibrated physics‐guided shear model incorporating Hertzian contact‐area scaling addresses the scale imbalance between normal and shear force signals, achieving a localization error of 0.47 mm and force estimation errors below 8%. The system is demonstrated through teleoperation of a six‐degree‐of‐freedom (6‐DoF) collaborative robot arm, illustrating its feasibility as a tactile command interface.