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Experimental study demonstrates multimodal tactile force and softness perception via a spiderweb-inspired electronic skin, suggesting scalable tactile sensing for robotics.
Electronic skin (e‐skin) that can conformably cover deformable surfaces is essential for robotic perception and wearable human–machine interfaces. However, simultaneously achieving high spatial resolution, multimodal sensing, and mechanical stretchability remains challenging. In addition, most existing machine‐learning‐based tactile systems rely on predefined material classifications, limiting their ability to recognize previously unseen objects. Here, we present a spiderweb‐inspired stretchable e‐skin that enables the perception of applied force, contact position, and object softness using a simple electrode design. The device is constructed using a conductive elastomer composite consisting to form a highly stretchable spiderweb‐like sensing network that can conform to three‐dimensional and deformable surfaces. By combining this structural design with a data‐driven learning framework based on reservoir computing, the system extracts rich spatiotemporal features from a limited number of sensing channels. The proposed platform reconstructs force distributions with an effective spatial resolution equivalent to a 6 × 6 pixel array using only eight electrodes while enabling quantitative prediction of applied force. Furthermore, object softness (including previously unseen materials) is quantitatively detected together with applied force. This approach significantly reduces hardware complexity while maintaining high sensing performance. The spiderweb e‐skin provides a scalable strategy for next‐generation tactile perception systems in various applications.
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Gao et al. (2026) studied this question.
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