Minzhi Xu
Papers
2
Total Citations
15
H-Index
2
About
Minzhi Xu is pioneering the next generation of soft, intelligent tactile sensors for robotics and biomedical applications. Their research centers on developing highly sensitive, flexible force and touch sensors that mimic human skin, leveraging advanced materials and deep learning to overcome longstanding limitations in automation and prosthetics. Xu’s most impactful work, “A Skin-Inspired PDMS Optical Tactile Sensor Driven by a Convolutional Neural Network” (2024), has already garnered 13 citations, demonstrating a novel fusion of optical fiber sensing with CNN-based signal interpretation to achieve robust, electromagnetic-interference-immune perception. This breakthrough addresses critical challenges in robotic manipulation and biomedical equipment integration. In “A Multiaxis Force Sensor Based on Pre-Strained Piezoresistive Film Strips” (2023), Xu tackled the cost and sensitivity trade-offs of carbon-based composites, advancing soft multi-axis force sensing for dexterous applications. By combining material innovation with machine learning, Xu’s work is setting new standards for tactile intelligence, enabling robots to interact with their environment more safely and precisely. Their contributions are shaping the future of soft robotics and human-machine interfaces, making them a rising figure in sensor engineering.
Research Focus
Key Achievements
Top Papers
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- 2