Abstract
Soft pneumatic actuators are one of the most promising actuation for soft robots, and great achievements have been obtained. But it remains challenging to endow sensing capabilities to pneumatic actuators, especially for the sensing ability originating directly from the actuator architecture. Herein, a self-sensing pneumatic torsional actuator (SPTA) is designed based on the electromagnetic induction effect and magnetically responsive materials. The SPTA can generate feedback voltage and current with the deformation, in which the sensing function comes from its inherent structure To investigate the mechanical and electrical characteristics, an experimental platform and a finite element model are established, respectively. We find that the torsion angle and output torque increase in nonlinear with the actuating pressure. The maximum torsion angle is 66.35°, which is 84.34% of that for the actuator fabricated by pure rubber. The maximum output torque (24.9 N mm) improves by 23.19% compared with the actuator made by pure rubber. As regards the electrical characteristics, the maximum feedback voltage and current are 2.90 µV and 29.50 nA when the SPTA is actuated by a pressure of −40 kPa. We also demonstrate that the relationship between the torsion angle and the magnetic flux change is approximately linear. Finally, the number of turns of wires, magnetic powders contents, and magnetic direction on the feedback voltage and current are studied. Results show that the feedback voltage and current can be enhanced by increasing the number of turns and magnetic powders contents. We envision that the SPTA would be promising for soft robots to realize their accuracy control and intelligentization.
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This work was supported by the Natural Science Foundation of Jiangxi Province of China (Grant No. 20232BAB214050) and the National Natural Science Foundation of China (Grant No. 52165004).
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Xiao, W., Hu, D., Hu, G. et al. Investigation of mechanical and electrical characteristics of self-sensing pneumatic torsional actuators. Sci. China Technol. Sci. 67, 130–142 (2024). https://doi.org/10.1007/s11431-023-2518-x
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DOI: https://doi.org/10.1007/s11431-023-2518-x