Peiyuan Li
Papers
2
Total Citations
6
H-Index
2
About
Peiyuan Li is a researcher at the forefront of intelligent tactile sensing, with a primary focus on fiber Bragg grating (FBG) technology and its integration with advanced deep learning models. Li’s major contributions lie in developing novel tactile perception systems that combine FBG sensors with transformer-based architectures, enabling precise material classification and object recognition. Their 2024 work, "Fiber Bragg grating tactile perception system based on cross-modal transformer," has already garnered 4 citations, while the complementary study "FBG Tactile Sensing System Based on SVP-Transformer for Material Classification" has received 2 citations, highlighting the growing interest in this emerging field. Li’s research addresses a critical gap in human-robot interaction by enhancing tactile sensory capabilities, which are essential for tasks like object grasping and environmental perception. By leveraging cross-modal learning, Li’s systems achieve superior accuracy in distinguishing materials, paving the way for more dexterous robotic hands and advanced prosthetics. This innovative fusion of photonic sensing and machine learning marks Li as a promising contributor to the future of intelligent tactile systems.
Research Focus
Key Achievements
Top Papers
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- 2