AI‐Enhanced Materials Identification with Smart Directional Tangential Flexible Sensor
Abstract In the field of intelligent manufacturing, flexible sensors play a key role as sensing components. However, people have previously focused on the normal response of tactile sensors and neglected the tangential response, and the traditional symmetric structure still has some difficulties in detecting the tangential force. Here, this work designed a novel sensor with high shear sensing capabilities using 3D printing technology to create micro‐pillar structures with adjustable aspect ratios, allowing for a wide detection range or high sensitivity. The sensor is composed of an anisotropic micro‐pillar dielectric layer and the fabric electrode layers. By vertically stacking two subunits, the sensor can accurately detect both the magnitude and direction of tangential forces. In addition, the sensor has virtually no signal drift after 20000 cycles, providing long‐term stability and durability. Finally, the sensor is integrated with AI technology and applied in areas such as robotic arm grasping, fabric texture sensing, and material recognition, highlighting its strong potential for applications in robotics and human‐machine interaction.
Authors
- Haoran Niu (ORCID: https://orcid.org/0000-0001-5522-8297)
- Bo Li (ORCID: https://orcid.org/0000-0003-2874-2391)
- P. L. Yu (ORCID: https://orcid.org/0000-0002-4660-6679)
- Haibo Luo
- Dong-Xing Zhang (ORCID: https://orcid.org/0000-0002-0253-5223)
- Qiuquan Guo (ORCID: https://orcid.org/0000-0001-8460-2110)
- Liwen Zhang (ORCID: https://orcid.org/0000-0003-3250-9867)
- Zhang Lin (ORCID: https://orcid.org/0000-0002-6600-2055)
Institutions
- University of Electronic Science and Technology of China (CN)
- Shenzhen Institute of Information Technology (CN)
Publication Details
- Journal
- Advanced Materials Technologies
- Published
- 2024-12-19
- DOI
- https://doi.org/10.1002/admt.202401164
- Citations
- 2
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.37
Funders
- Basic and Applied Basic Research Foundation of Guangdong Province