Ying Mingfeng
Papers
1
Total Citations
2
H-Index
1
About
Ying Mingfeng is a researcher specializing in robotic mechanism design and multi-objective performance optimization. His work focuses on enhancing the kinematic performance of industrial robots through systematic analysis and algorithmic optimization. In his most-cited study (2016), he introduced a novel framework that simultaneously optimizes three critical kinematic indices—global kinematic average, volatility, and worst-case values—using multi-objective optimization algorithms. By treating robot link lengths as design variables, his approach enables more balanced and robust performance across diverse operational conditions. This contribution addresses a key challenge in robotics: achieving high precision and stability without sacrificing efficiency. Although his citation count is currently modest, his work lays important groundwork for future advancements in robot kinematics and design optimization. Researchers and students in robotics and mechanical engineering will find his methodology valuable for developing more adaptive and high-performing robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Multi-objective performance optimization of robotic mechanism2 citations · 2016