• • The 3DAE-Skin employs an eight-arm cage-like mesoscopic structure with a height of 600 μm and an arched mesoscopic structure with a height of 250 μm, enabling spatial decoupling of normal force, shear force, and strain within a 5×5 sensing unit array. This precise geometric arrangement directly addresses the cross-talk bottleneck that has historically limited multimodal electronic skins to laboratory demonstrations, providing a manufacturable topology for industrial tactile sensors.
• • A gradient modulus encapsulation strategy uses high-modulus PDMS for force transducers and low-modulus Ecoflex for strain sensors, replicating the mechanical contrast between collagen fiber networks and dermal matrix. This material selection is critical for maintaining independent sensing channels under complex loading, as it prevents strain-induced artifacts in force measurements and enables reliable decoupling without complex signal post-processing.
• • The heterostack comprises five polyimide dielectric layers, two force sensing layers, and two strain sensing layers, achieving a multi-layer architecture that mimics the 3D distribution of Merkel cells and Ruffini endings. This layer count and arrangement provide a concrete design rule for balancing electrical isolation, mechanical compliance, and sensing density, which is essential for scaling to higher-resolution arrays without sacrificing decoupling performance.
• • The integration of deep learning algorithms within the multi-point tactile perception system ensures robustness when some sensors fail, as explicitly stated in the optimization roadmap. This algorithmic resilience is industrially significant because it reduces the need for redundant sensor hardware, lowering bill-of-materials costs and improving fault tolerance in robotic grippers and prosthetic limbs where sensor degradation is inevitable.