Merkel's Disks Bioinspired Self‐Powered Flexible Magnetoelectric Sensors Toward the Robotic Arm's Tactile Perceptual Functioning and Smart Learning
Zheng Ma, Jingwei Ai, Xuan Zhang, Zhuolin Du, Zhenhua Wu, Kun Wang, Dezhi Chen, Bin Su
- Year
- 2019
- Citations
- 40
- Access
- Open access
Abstract
Flexible/soft tactile sensors enable the robotic arms to gain real‐time mechanical responses, which are of utmost importance for future deep learning in robotic sciences and technologies. Learning from nature will inspire the advances of soft tactile sensors as mother nature is proficient in achieving unique functionality at the simplest construction. Herein, the fabrication of self‐powered soft tactile sensors is reported. The shape of flexible sensors mimics Merkel's disks, allowing for a well tactile perceptual functionality. Due to the use of flexible magnetoelectric materials, the sensors are self‐powered without external power supply. This unique functionality is explained by Maxwell's numerical simulation, allowing for further improvement of their performance by adjusting diverse fabrication factors. Furthermore, such self‐powered soft tactile sensors are attached to the tips of a robotic arm, enabling the arm to distinguish different objects after smart learning. The soft sensor design reported here is expected to manifest in a range of self‐powered sensing systems, opening up as yet unexplored avenues for the development and the exploitation of future intelligent robots and their deep learning.
Keywords
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