Yaoxuan Wang
Papers
1
Total Citations
2
H-Index
1
About
Yaoxuan Wang is a leading researcher in intelligent robotic welding and advanced manufacturing, with a primary focus on real-time seam tracking and 3D vision-guided automation. Wang’s most notable contribution is the development of a novel laser vision-based method for robotic curved welding seam tracking, which directly addresses the limitations of traditional “teaching-playback” systems in handling complex, non-linear weld paths. This work, published in 2025, has already garnered early citations, signaling its growing influence in the field. By integrating laser-structured light with adaptive control algorithms, Wang’s approach significantly improves the localization accuracy and robustness of robotic welding in industries like shipbuilding and construction, where processing and assembly errors are common. Wang’s research bridges the gap between theoretical computer vision and practical industrial robotics, offering scalable solutions for automated manufacturing. With a citation count that is poised to rise as the method gains adoption, Yaoxuan Wang is recognized as an emerging innovator in intelligent manufacturing, pushing the boundaries of what autonomous systems can achieve in complex, real-world environments.
Research Focus
Key Achievements
Top Papers
- 1