Guodong Yi
Papers
2
Total Citations
9
H-Index
2
About
Guodong Yi is a leading researcher in intelligent manufacturing and robotics, whose work focuses on enhancing the efficiency and quality of automated systems through advanced algorithmic design. His primary research areas include multiobjective path planning, additive manufacturing process optimization, and computational geometry for 3D printing. Yi’s major contributions are exemplified by his multiobjective path-smoothing algorithm, which simultaneously reduces computational complexity, improves path security, and minimizes execution time for mobile robots—a critical advancement for autonomous navigation in dynamic environments. This work has garnered 7 citations, reflecting its immediate relevance to the field. In additive manufacturing, Yi pioneered a multi-orientation adaptive slicing and path generation method that leverages support constraints and relationship matrices to mitigate the step effect and reduce material waste in fused deposition modeling. By resolving path interference issues in multi-orientation printing, his approach significantly enhances surface quality and lowers consumables cost, earning 2 citations for its novel integration of geometric reasoning with manufacturing constraints. Yi’s research bridges theoretical optimization with practical robotic and manufacturing applications, offering scalable solutions that advance both autonomous systems and sustainable production. His work continues to influence the development of smarter, more efficient manufacturing pipelines.
Research Focus
Key Achievements
Top Papers
- 1
- 2