Xueyan Han
Papers
1
Total Citations
23
H-Index
1
About
Xueyan Han is a researcher specializing in motion planning and optimization for robotic mechanisms, with a particular focus on improving the stability and precision of pointing systems. Her most-cited work introduces a novel hybrid interpolation algorithm combined with the NSGA-II multi-objective optimization framework to generate smooth, jerk-continuous trajectories in joint space. By addressing the critical need for continuous jerk to enhance motion stability—a challenge that typically demands computationally intensive higher-order polynomials or B-splines—Han’s approach reduces calculation overhead while achieving superior performance. This contribution, published in 2020 and garnering 23 citations, underscores her ability to bridge algorithmic innovation with practical engineering demands. Her research is instrumental for applications in aerospace, robotics, and precision instrumentation, where smooth, reliable motion is paramount. Han’s work exemplifies a methodical approach to solving complex optimization problems, making her a notable figure in the field of robotic trajectory planning.
Research Focus
Key Achievements
Top Papers
- 1