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<p>Developing microsystem-based tactile sensors that can simultaneously decode multidirectional forces and precise contact locations remains a formidable challenge, limiting robotic dexterity and human–machine interaction. To bridge this gap, we present HexaTouch, a fingertip-scale (15 × 15 × 8 mm) sensor that synergizes the deformation-encoding principle of vision-based sensors with the miniaturization and rapid response of capacitive sensing. The core is a bioinspired bilayer elastomer monolithically incorporating a graded micropillar array, which creates spatially heterogeneous stiffness to enhance sensitivity and load tolerance while generating rich deformation patterns in response to mechanical stimuli. These local deformations are directly transduced into high-resolution capacitive images via a dense capacitive micro-array. A dedicated machine learning framework decodes these images into six-axis force/torque vectors (<i>Fx</i>, <i>Fy</i>, <i>Fz</i>, <i>Mx</i>, <i>My</i>, <i>Mz</i>) and three-dimensional contact coordinates (<i>x</i>, <i>y</i>, <i>z</i>). Experimental results demonstrate exceptional performance, with force measurement errors under 1.6%, contact localization precision of up to 0.1 mm, and inference latency of only 1.5 ms. The system maintains high stability across 0–40 °C and 40–90% relative humidity, with mechanical robustness confirmed through 10-day cumulative cyclic loading tests. The versatility of this sensing system is further validated through extensive applications, including dexterous grasping with stability assessment, precise peg-in-hole assembly under misalignment, and intuitive human-machine interaction in drone flight control and virtual gaming. HexaTouch therefore provides a robust, adaptable micro-tactile sensing platform that significantly advances robotic manipulation and environmental interaction.</p><p></p>

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Fingertip-scale six-axis tactile interface with high-precision force sensing and position localization for dexterous human–machine interactions

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月20日

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  • Yi Song,
  • Junwei Wang,
  • Zongke Li,
  • Weilang Hu,
  • Ye Qiu,
  • Ye Tian,
  • Pei Zhao,
  • Aiping Liu,
  • Huaping Wu

摘要

Developing microsystem-based tactile sensors that can simultaneously decode multidirectional forces and precise contact locations remains a formidable challenge, limiting robotic dexterity and human–machine interaction. To bridge this gap, we present HexaTouch, a fingertip-scale (15 × 15 × 8 mm) sensor that synergizes the deformation-encoding principle of vision-based sensors with the miniaturization and rapid response of capacitive sensing. The core is a bioinspired bilayer elastomer monolithically incorporating a graded micropillar array, which creates spatially heterogeneous stiffness to enhance sensitivity and load tolerance while generating rich deformation patterns in response to mechanical stimuli. These local deformations are directly transduced into high-resolution capacitive images via a dense capacitive micro-array. A dedicated machine learning framework decodes these images into six-axis force/torque vectors (Fx, Fy, Fz, Mx, My, Mz) and three-dimensional contact coordinates (x, y, z). Experimental results demonstrate exceptional performance, with force measurement errors under 1.6%, contact localization precision of up to 0.1 mm, and inference latency of only 1.5 ms. The system maintains high stability across 0–40 °C and 40–90% relative humidity, with mechanical robustness confirmed through 10-day cumulative cyclic loading tests. The versatility of this sensing system is further validated through extensive applications, including dexterous grasping with stability assessment, precise peg-in-hole assembly under misalignment, and intuitive human-machine interaction in drone flight control and virtual gaming. HexaTouch therefore provides a robust, adaptable micro-tactile sensing platform that significantly advances robotic manipulation and environmental interaction.