Researchers from Zhejiang University utilized a support vector machine algorithm to optimize the parameters of a triboelectric nanogenerator tactile sensor. Compared to traditional experience-driven design methods, this study integrated design with algorithms, adopting a data-driven approach to optimize the sensor's parameters. The optimized sensor can accurately recognize various touch patterns and has achieved text and Braille recognition. This design approach is expected to shorten the sensor's development cycle, reduce costs, and expand its applications in areas such as human-computer interaction.
Zhejiang University Research Team Optimizes Tactile Sensor Design Using Machine Learning Algorithms
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