Meixuan Lv
Papers
1
Total Citations
2
H-Index
1
About
Meixuan Lv is a rising researcher at the forefront of robotic perception, specializing in vision-based tactile sensing and multimodal sensor simulation. Her most-cited work, "Vision-Based Tactile Image Generation via Contact Condition-Guided Diffusion Model" (2025), introduces a groundbreaking diffusion model that generates realistic tactile images guided by contact conditions, enabling robots to perceive object geometry and force information through high-resolution optical measurements. This innovation bridges the gap between visual and tactile data, offering a scalable simulation framework that reduces reliance on costly physical sensors. With early citations already highlighting its impact, Lv’s contributions are poised to advance dexterous manipulation and human-robot interaction. Her research addresses a critical challenge in robotics—synthesizing high-fidelity tactile feedback for training and control—making her a key figure in the growing field of embodied AI. As her work gains traction, Lv is shaping the future of how robots understand and interact with their physical environment.
Research Focus
Key Achievements
Top Papers
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