Guanxin Chi
Papers
2
Total Citations
7
H-Index
2
About
Guanxin Chi is a pioneering researcher in intelligent robotic welding and advanced manufacturing, whose work bridges the gap between automation and real-world industrial complexity. His primary research areas include 3D scanning-based robotic trajectory planning, multi-layer multi-pass welding, and dual-modal perception systems integrating stereo vision with deep learning. Chi’s major contributions lie in overcoming the limitations of traditional offline programming for large, asymmetric workpieces—such as those with significant machining or assembly deviations—by developing methods that generate accurate STL models for precise welding paths. His 2025 paper on handheld 3D scanning for large intersecting line workpieces (4 citations) demonstrates a novel approach to multi-bead welding, while his dual-modal framework (3 citations) tackles robustness issues in teaching-free trajectory generation by combining 2D image recognition with 3D point cloud planning. Though early in citation impact, these works represent a significant leap in adaptive, vision-guided automation for heavy manufacturing. Chi’s research is notable for its practical applicability, offering scalable solutions for industries requiring high-precision welding of complex geometries. His innovative fusion of deep learning and 3D sensing positions him as a rising leader in smart robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2