Yuhang Wan
Papers
1
Total Citations
3
H-Index
1
About
Yuhang Wan is a researcher in robotics and intelligent control systems, with a primary focus on optimizing multi-degree-of-freedom manipulators for enhanced precision and efficiency. Their most notable contribution is the development of an enhanced particle swarm optimization (PSO) algorithm for six-degree-of-freedom robotic arms, which dynamically adjusts inertia weights to improve joint angle path planning and end-effector accuracy. This work, published in 2024, has already garnered 3 citations, signaling early impact in the field of robotic motion optimization. Wan's research addresses critical challenges in industrial automation, particularly the trade-off between computational efficiency and trajectory precision. By refining swarm intelligence techniques for real-world robotic applications, they contribute to advancing autonomous manipulation systems. Their work is especially relevant for researchers exploring evolutionary algorithms in robotics, offering a practical framework for reducing positional errors in complex kinematic chains. As a rising voice in optimization-based robotics, Yuhang Wan continues to push the boundaries of how intelligent algorithms can enhance mechanical system performance.
Research Focus
Key Achievements
Top Papers
- 1