Pengsheng Huang
Papers
1
Total Citations
30
H-Index
1
About
Pengsheng Huang is a robotics researcher whose work centers on industrial robot motion planning and trajectory optimization. His most influential contribution, the 2021 paper "An Analytical Method for Decoupled Local Smoothing of Linear Paths in Industrial Robots," has garnered 30 citations, establishing a foundational approach for enhancing robot efficiency and precision. Huang’s key research areas include path smoothing algorithms, decoupled control strategies, and local optimization techniques for robotic manipulators. By developing an analytical method that separates global path planning from local smoothing, he addresses critical challenges in industrial automation—reducing computational complexity while maintaining smooth, collision-free motion. This work is particularly valuable for high-speed manufacturing environments where abrupt path changes cause wear, energy loss, or positioning errors. Huang’s decoupled approach enables real-time adjustments without compromising overall trajectory integrity, making it practical for deployment in assembly lines and material handling systems. His research bridges theoretical kinematics with applied robotics, offering engineers a scalable solution for improving robot performance. With continued impact in the field, Huang’s contributions are shaping the next generation of adaptive, efficient industrial robots.
Research Focus
Key Achievements
Top Papers
- 1