Weiliang Xu
Papers
4
Total Citations
47
H-Index
3
About
Weiliang Xu is a pioneering researcher at the intersection of tactile sensing, robotic perception, and human-robot collaboration. His work centers on developing intelligent sensing systems that enable robots to perceive and interact with their environment with unprecedented sophistication. Xu’s major contributions include the creation of a vision-based tactile sensing system that uses neural networks to decode multimodal contact information—a breakthrough that has garnered 23 citations since 2024. He has also advanced the field of kinesthetic perception through differential sensor design, using machine learning to classify and decouple complex motion data, a method cited 14 times. More recently, Xu has pushed the boundaries of human-robot collaboration by integrating large vision-language models for 6D pose estimation of novel objects, enabling robots to work alongside humans with remarkable adaptability. His work on generating vision-based tactile images using diffusion models further demonstrates his commitment to bridging simulation and reality. With a growing citation impact and a clear trajectory toward more generalizable, intelligent robotic systems, Xu is shaping the future of how machines sense and interact with the physical world.
Research Focus
Key Achievements
Top Papers
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