TY - JOUR
T1 - Fingerprint-inspired biomimetic tactile sensors for the surface texture recognition
AU - Qin, Liguo
AU - Hao, Luxin
AU - Huang, Xiaodong
AU - Zhang, Rui
AU - Lu, Shan
AU - Wang, Zheng
AU - Liu, Jianbo
AU - Ma, Zeyu
AU - Xia, Xiaohua
AU - Dong, Guangneng
N1 - Publisher Copyright:
© 2024 Elsevier B.V.
PY - 2024/6/1
Y1 - 2024/6/1
N2 - A bionic tactile device is designed for object surface texture recognition, taking inspiration from the microstructure of human fingerprints. The sense of touch in humans is achieved through the frictional vibration and generation of electrical potential signals by subcutaneous receptors. Constructing a tactile sensing device involves generating distinct signals upon interacting with different materials. The piezoelectric film PVDF is particularly suitable as a sensitive material for sensors due to its excellent flexibility, strong mechanical strength, excellent dynamic response and cost-effectiveness. This paper presents the design of a PVDF-based fingerprint-inspired tactile sensor capable of differentiating various textures. By combining the collected signals with machine learning algorithms, diverse textures can be effectively identified. To demonstrate the sensor's superior performance, two experiments were conducted—one focused on recognizing different material textures, and the other on recognizing Braille characters. The accuracy achieved in these experiments was 97.4% and 96.5%, respectively, highlighting the technology's significant potential in intelligent robotics and human-computer interaction.
AB - A bionic tactile device is designed for object surface texture recognition, taking inspiration from the microstructure of human fingerprints. The sense of touch in humans is achieved through the frictional vibration and generation of electrical potential signals by subcutaneous receptors. Constructing a tactile sensing device involves generating distinct signals upon interacting with different materials. The piezoelectric film PVDF is particularly suitable as a sensitive material for sensors due to its excellent flexibility, strong mechanical strength, excellent dynamic response and cost-effectiveness. This paper presents the design of a PVDF-based fingerprint-inspired tactile sensor capable of differentiating various textures. By combining the collected signals with machine learning algorithms, diverse textures can be effectively identified. To demonstrate the sensor's superior performance, two experiments were conducted—one focused on recognizing different material textures, and the other on recognizing Braille characters. The accuracy achieved in these experiments was 97.4% and 96.5%, respectively, highlighting the technology's significant potential in intelligent robotics and human-computer interaction.
KW - Bionic tactile device
KW - Machine learning
KW - Texture recognition
UR - https://www.scopus.com/pages/publications/85188522003
U2 - 10.1016/j.sna.2024.115275
DO - 10.1016/j.sna.2024.115275
M3 - 文章
AN - SCOPUS:85188522003
SN - 0924-4247
VL - 371
JO - Sensors and Actuators A: Physical
JF - Sensors and Actuators A: Physical
M1 - 115275
ER -