Affiliation:
1. Department of Electronic Science Xiamen University Xiamen 361005 China
2. Academy for Advanced Interdisciplinary Science and Technology Key Laboratory of Advanced Materials and Devices for Post‐Moore Chips Ministry of Education University of Science and Technology Beijing Beijing 100083 China
3. Beijing Key Laboratory for Advanced Energy Materials and Technologies School of Materials Science and Engineering University of Science and Technology Beijing Beijing 100083 China
4. School of Electrical and Electronic Engineering Nanyang Technological University Singapore 639798 Singapore
Abstract
AbstractTouch control intention recognition is an important direction for the future development of human–machine interactions (HMIs). However, the implementation of parallel‐sensing functional modules generally requires a combination of different logical blocks and control circuits, which results in regional redundancy, redundant data, and low efficiency. Here, a location‐and‐pressure intelligent tactile sensor (LPI tactile sensor) unprecedentedly combined with sensing, computing, and logic is proposed, enabling efficient and ultrahigh‐resolution action–intention interaction. The LPI tactile sensor eliminates the need for data transfer among the functional units through the core integration design of the layered structure. It actuates in‐sensor perception through feature transmission, fusion, and differentiation, thereby revolutionizing the traditional von Neumann architecture. While greatly simplifying the data dimensionality, the LPI tactile sensor achieves outstanding resolution sensing in both location (<400 µm) and pressure (75 Pa). Synchronous feature fusion and decoding support the high‐fidelity recognition of action and combinatorial logic intentions. Benefiting from location and pressure synergy, the LPI tactile sensor demonstrates robust privacy as an encrypted password device and interaction intelligence through pressure enhancement. It can recognize continuous touch actions in real time, map real intentions to target events, and promote accurate and efficient intention‐driven HMIs.
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Cited by
1 articles.
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