Three-Dimensional Flexible Tactile Sensor Arrays for Perceptual Grasping: Towards Enhanced Perceptual Robotics

Recent advancements in intelligent robotics have substantially heightened the demand for multidimensional haptic sensors. Traditional haptic sensors are constrained by their sensitivity, anti-interference capabilities, and measurement range, thereby limiting their application in complex environments. Inspired by the structure of human skin, a three-dimensional arrayed magnetic sensor (MCE) was developed, exhibiting high sensitivity (57.625N<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup>), a wide force measurement range, low hysteresis (1.04%), and high stability. The sensor comprises a three-layer design: the top layer includes a flexible square magnet that deforms under external forces to detect normal and tangential forces; the middle layer incorporates a flexible elastomer (Ecoflex 00-30) combined with a spring to achieve a broad range of force measurements; and the bottom layer consists of a flexible circuit board (FPCB) embedded with an array of Hall sensors to convert magnetic field variations into electrical signals. The normal force measurement range of the MCE sensor spans from 0 to 16 N, with a minimum resolution of 10 mN, enabling the accurate detection of minor force variations. The tangential force is measured within a range of –7 N to 7 N. Experimental findings indicate that the MCE sensor enables real-time slip detection and, when integrated with deep learning algorithms, attains a remarkable object recognition accuracy of 96.36%. This technological progression significantly augments tactile sensing functionalities, thereby facilitating advancements in intelligent robotics, such as precision grasping, and enhancing human-machine interaction, particularly in the realm of medical rehabilitation devices.

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Publication Details

Journal
IEEE Sensors Journal
Published
2025-01-01
DOI
https://doi.org/10.1109/jsen.2025.3559343
Citations
2
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
1.35

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article

Three-Dimensional Flexible Tactile Sensor Arrays for Perceptual Grasping: Towards Enhanced Perceptual Robotics

Xu-Dong Hou, Shaoyu Liu, Xingang Zhao, Daohui Zhang et al.
2 citations
IEEE Sensors Journal
Advanced Sensor and Energy Harvesting Materials
1.35
article

Three-Dimensional Flexible Tactile Sensor Arrays for Perceptual Grasping: Towards Enhanced Perceptual Robotics

Xu-Dong Hou, Shaoyu Liu, Xingang Zhao, Daohui Zhang, Naijia Xu, Xin Fu, Bo Han
article en
2 citations

Abstract

Recent advancements in intelligent robotics have substantially heightened the demand for multidimensional haptic sensors. Traditional haptic sensors are constrained by their sensitivity, anti-interference capabilities, and measurement range, thereby limiting their application in complex environments. Inspired by the structure of human skin, a three-dimensional arrayed magnetic sensor (MCE) was developed, exhibiting high sensitivity (57.625N<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup>), a wide force measurement range, low hysteresis (1.04%), and high stability. The sensor comprises a three-layer design: the top layer includes a flexible square magnet that deforms under external forces to detect normal and tangential forces; the middle layer incorporates a flexible elastomer (Ecoflex 00-30) combined with a spring to achieve a broad range of force measurements; and the bottom layer consists of a flexible circuit board (FPCB) embedded with an array of Hall sensors to convert magnetic field variations into electrical signals. The normal force measurement range of the MCE sensor spans from 0 to 16 N, with a minimum resolution of 10 mN, enabling the accurate detection of minor force variations. The tangential force is measured within a range of –7 N to 7 N. Experimental findings indicate that the MCE sensor enables real-time slip detection and, when integrated with deep learning algorithms, attains a remarkable object recognition accuracy of 96.36%. This technological progression significantly augments tactile sensing functionalities, thereby facilitating advancements in intelligent robotics, such as precision grasping, and enhancing human-machine interaction, particularly in the realm of medical rehabilitation devices.

IEEE Sensors Journal
Shenyang Institute of Automation (CN), Shenyang University of Technology (CN), Chinese Academy of Sciences (CN), Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Affordable and clean energy
Openalex Percentile: Top 21%
Advanced Sensor and Energy Harvesting Materials
1.35
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