Jingwen Tong
Papers
1
Total Citations
2
H-Index
1
About
Jingwen Tong is a researcher whose work sits at the intersection of industrial robotics, 3D modeling, and automated manufacturing. His primary research areas include robotic path planning, feature extraction from 3D models, and the optimization of redundant degrees of freedom in industrial robots. Tong’s most notable contribution is his development of an automatic tool path planning strategy that leverages feature extraction from 3D models, specifically addressing the redundant sixth axis in 6R industrial robots used for tasks like grinding, welding, and spraying. By exploiting this redundancy, his work enables more efficient orientation planning without compromising the fixed end-effector direction required in these applications. While his most-cited paper has garnered 2 citations, it represents a foundational step in reducing manual programming effort and improving robot autonomy in manufacturing. Tong’s research is particularly valuable for students and engineers seeking to bridge the gap between CAD-based design and real-world robotic execution, offering a systematic approach to path generation that enhances both flexibility and precision in industrial settings.
Research Focus
Key Achievements
Top Papers
- 1