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May 26, 2026Small0 citations

Bioinspired High‐Resolution, Wide‐Range Pressure Sensor Enabled by Synergistic CB/CNT Island‐Chain and PVDF/PDMS Fiber Network for Dexterous Robotic Hands

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PCPeng ChengJHJinhua HongYHYaofeng Hu

Key Points

  • The research aims to develop a high-resolution and wide-range flexible pressure sensor for dexterous robotic hands.
  • Designed a bioinspired two-layer flexible pressure sensor integrating a CB/CNT island-chain and PVDF/PDMS fiber network.
  • Achieved a spatial resolution of 80 cm−2 with a rhombic grid electrode design.
  • Tested the sensor's performance over 10,000 cycles for stability and low detection limits.
  • Achieved a wide pressure range up to 500 kPa with a sensitivity of 2.391 kPa−1.
  • Demonstrated low detection limits of 0.0013 N (19 Pa) and stable performance.
  • Enabled real-time pressure mapping and contour recognition in robotic hands.

Abstract

ABSTRACT The integration of flexible electronics and robotics is critical for intelligent sensing in dexterous hands, where flexible pressure sensors enable precise grasping. However, existing pressure sensors are limited by low spatial resolution and the trade‐off between sensitivity and pressure range. Here, we propose a bioinspired high‐resolution, wide‐range flexible pressure sensor based on a synergistic CB/CNT island‐chain and PVDF/PDMS fibrous network. The two‐layer architecture, inspired by human skin, incorporates a rhombic grid electrode design, achieving a spatial resolution of 80 cm − 2 at the fingertip. The PVDF/PDMS fibrous network provides elasticity and cushioning, while the CB/CNT island‐chain structure enables complementary conductive behavior, resulting in a wide pressure range (up to 500 kPa) and high sensitivity (2.391 kPa − 1 ). The sensor also exhibits low detection limits (0.0013 N, 19 Pa) and stable performance over 10 000 cycles. Integrated into a dexterous robotic hand, the sensor enables real‐time pressure mapping, contour recognition, and object property differentiation, demonstrating its potential for applications in intelligent robotics and industrial automation.

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Cite This Study

Cheng et al. (2026) studied this question.

synapsesocial.com/papers/6a153a88b5d9c58d83e8d0adhttps://doi.org/10.1002/smll.73918
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