Papers
6
Total Citations
50
H-Index
3
About
Ning Xiao is a robotics researcher whose work bridges the critical gap between theoretical control and practical industrial application. His primary research areas include humanoid locomotion, dual-arm cooperative robotics, and precision manufacturing, with a particular focus on trajectory optimization and stiffness-enhanced robotic systems. Xiao’s most influential work, “Multi-objective adaptive trajectory optimization for industrial robot based on acceleration continuity constraint,” has garnered 24 citations and addresses fundamental challenges in smooth, efficient robot motion planning. He made significant contributions to humanoid walking stability through an improved model predictive control method based on the Divergent Component of Motion (DCM), enabling robust locomotion under external interference. In industrial robotics, Xiao proposed a novel high-stiffness 6-DOF dual-arm cooperative robot optimized for blade polishing, overcoming the traditional serial arm limitations of poor absolute positioning accuracy. His more recent work explores RGB-based 6D pose estimation using transformer networks for robotic grasping, and Pareto-optimal fractional-order admittance control for precision polishing. With publications spanning 2022 to 2025, Xiao’s research demonstrates a clear trajectory toward integrating advanced control theory, optimization, and perception for next-generation manufacturing and service robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Robust Walking for Humanoid Robot Based on Divergent Component of Motion10 citations · 2022
- 3
- 4
- 5
- 6