Dezhi Liu
Papers
1
Total Citations
16
H-Index
1
About
Dezhi Liu is a researcher in intelligent manufacturing and robotic automation, with a primary focus on optimizing spray painting processes for complex surfaces. His key contributions lie in trajectory planning for industrial robots, particularly addressing the challenge of coating irregular planes efficiently. In his most-cited work, "Trajectory Planning of Spray Gun With Variable Posture for Irregular Plane Based on Boundary Constraint" (2021, 16 citations), Liu proposed a novel method that dynamically adjusts spray gun posture to minimize overspray and paint waste, directly tackling the inefficiencies of conventional fixed-angle approaches. By incorporating boundary constraints into the planning algorithm, his research enhances coating uniformity while reducing material costs—a critical advancement for industries like automotive manufacturing. This work demonstrates his ability to bridge theoretical optimization with practical industrial needs. Liu’s research has been recognized for its potential to improve both productivity and sustainability in automated painting systems, making him a notable contributor to the field of robotic path planning and surface coating technology.
Research Focus
Key Achievements
Top Papers
- 1