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Bioinspired Electrostatic-Field Perturbated Sensing for General Material Noncontact Perception
Weiqiang Zhang1, Mingxin Liu1, Xiaozhou Lü1
1School of Aerospace Science and Technology, Xidian University, Xi'an, China.
None:
Noncontact sensing is essential for smart manufacturing and safe human-machine interaction, yet existing proximity and inspection sensors are often limited by material selectivity, ambient light, and continuous power consumption. Here, we report a bioinspired electrostatic-field sensor that implements a solid-state analogue of electrolocation using a corona-polarized fluoropolymer electret. The pre-charged electret establishes a quasi-static electric field, and nearby objects reshape this field to induce measurable potential modulation on a grounded electrode, enabling friction-free sensing without active emission or mechanical contact. The sensor detects both conductive and dielectric targets (metals, polymers, glass), while waveform features encode material-dependent electrical signatures. The device achieves a near-field change in separation sensitivity of 1.05 V per 50 µm and maintains stable responses over 10,000 approach-withdraw cycles. Combined with machine-learning models, the platform enables proximity warning, touch-free interaction, material discrimination, coating-defect recognition, gesture decoding, and gesture-to-robot control. This work establishes electrostatic-field perturbation as a robust strategy for low-power, multifunctional noncontact perception.
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