Mechanically Decoupled Multimodal Tactile Perception Enabled by a Janus Textile Architecture

Abstract

Tactile perception of surface properties is crucial for advanced robotics, yet conventional multimodal sensors suffer from mechanically coupled transduction that causes stress dissipation, signal interference, and complex decoupling. Here, we report a Janus-structured textile sensor that enables mechanically selective multimodal perception via physically decoupled force pathways. The Janus architecture integrates a conductive layer responsive to normal compression and a polydimethylsiloxane (PDMS)-coated dielectric layer sensitive to sliding, intrinsically separating piezoresistive and triboelectric signals without algorithmic decoupling. This structurally decoupled design effectively suppresses stress dissipation, enhances stress-transfer efficiency, and generates intrinsically distinguishable tactile signal fingerprints without relying on complex algorithmic decoupling. Benefiting from this mechanically selective transduction mechanism, the sensor exhibits excellent static and dynamic sensing capability, together with robust hydrophobicity, self-cleaning capability, and abrasion resistance. Assisted by machine learning-enabled feature analysis, the sensor achieves recognition accuracies of 99.6% for texture classification and 94.5% for material identification across 21 distinct samples. Furthermore, an integrated robotic tactile cognition system is constructed, enabling closed-loop tactile sensing especially the simultaneous surface texture and material recognition. This work establishes a mechanically selective tactile transduction strategy for physically separated multimodal perception, providing a scalable platform for next-generation robotic skins, embodied perception systems, and intelligent human–machine interfaces.

Graphical abstract

Keywords

Textile / Janus structure / Tactile sensor / Machine learning / Surface recognition

References

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Funding

National Natural Science Foundation of China(52303051)

Rights & permissions

Donghua University, Shanghai, China