期刊
ACS APPLIED MATERIALS & INTERFACES
卷 13, 期 47, 页码 56320-56328出版社
AMER CHEMICAL SOC
DOI: 10.1021/acsami.1c17506
关键词
triboelectric nanogenerators; electronic skin; multidimensional force sensor; robotics; tactile sensing
资金
- National Natural Science Foundation of China [U2013213, 51820105008, 92048302]
- Technology Innovation Project of Hubei Province of China [2019AEA171]
- Open Research Foundation of State Key Laboratory of Digital Manufacturing Equipment Technology [DMETKF2020014]
By using a single-electrode-mode triboelectric nanogenerator (S-TENG), a fully elastic E-skin capable of sensing both normal pressure and shear force simultaneously has been developed. The pressure sensor shows high linearity and sensitivity in the low-pressure region, while the multidimensional force sensor utilizes two S-TENGs to detect normal pressure and shear force separately. When mounted on a robotic manipulator, the sensor can recognize changes in grabbing state, suggesting potential applications in robotics, human-robot interactions, environmental awareness, and object recognition.
The ability to detect multidimensional forces is highly desired for electronic skin (E-skin) sensors. Here, based on single-electrode-mode triboelectric nanogenerators (S-TENGs), fully elastic E-skin that can simultaneously sense normal pressure and shear force has been proposed. With the hemispherical curve-structure design and further structural optimization, the pressure sensor exhibits a high linearity and sensitivity of 144.8 mV/kPa in the low-pressure region. By partitioning the lower tribolayer into two symmetric parts, a multidimensional force sensor has been fabricated in which the output voltage sum and ratio of the two S-TENGs can be used for normal pressure and shear force sensing, respectively. When the multi-dimensional force sensors are mounted at a two-fingered robotic manipulator, the change of the grabbing state can be recognized, indicating that the sensor may have great application potential in tactile sensing for robotic manipulation, human-robot interactions, environmental awareness, and object recognition.
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