Yusen Wu
Papers
2
Total Citations
6
H-Index
2
About
Yusen Wu is a rising researcher in intelligent robotic welding, specializing in the integration of computer vision and automation for complex manufacturing environments. His work focuses on two key challenges: enabling robots to perceive and navigate unstructured welding scenes, and achieving precise tracking of curved seams. Wu’s most cited paper, “Path planning method of welding robot based on point cloud scene understanding” (2025, 4 citations), introduces a novel approach that uses 3D point cloud data to allow robots to autonomously interpret their surroundings and plan optimal welding paths—a critical advancement for industries like shipbuilding and construction, where workpiece geometry is irregular. His second highly cited work, “A novel laser vision-based method for robotic curved welding seam tracking” (2025, 2 citations), addresses the limitations of traditional “teaching-playback” systems by proposing a laser vision sensor that adapts in real-time to processing and assembly errors in curved seams. Though early in his career, Wu’s contributions are already gaining attention for their potential to improve welding accuracy and flexibility. His research promises to reduce reliance on manual programming and enhance the adaptability of robotic welding in real-world industrial settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2