Yongqing Yu
Papers
1
Total Citations
16
H-Index
1
About
Yongqing Yu is a researcher focused on advancing robotic automation for industrial manufacturing, with a particular emphasis on spray painting processes. Their key research areas include trajectory planning, spray gun posture optimization, and boundary-constrained path generation for complex surfaces. Yu’s most notable contribution is the development of a novel method for trajectory planning of spray guns with variable posture on irregular planes, addressing the critical industry challenge of overspray—which leads to low efficiency and excessive paint waste. By integrating boundary constraints into the planning algorithm, Yu’s work enables robots to dynamically adjust spray gun orientation, significantly improving coating uniformity and material utilization on non-planar surfaces. This research, published in 2021, has garnered 16 citations, reflecting its practical relevance for automotive and aerospace manufacturing. Yu’s achievements demonstrate a strong ability to bridge theoretical optimization with real-world industrial constraints, offering tangible solutions for reducing waste and enhancing productivity in automated painting systems. Their work continues to influence the development of smarter, more adaptive robotic manufacturing technologies.
Research Focus
Key Achievements
Top Papers
- 1