Yusong Xiao
Papers
1
Total Citations
14
H-Index
1
About
Yusong Xiao is a researcher in robotics and control systems, with a primary focus on dynamic parameter identification and optimization for industrial robotic arms. His most-cited work, "Dynamic parameter identification based on improved particle swarm optimization and comprehensive excitation trajectory for 6R robotic arm" (2023), addresses the growing demand for higher control precision in complex robotic environments. In this study, Xiao developed a novel method combining an improved particle swarm optimization algorithm with a comprehensive excitation trajectory to accurately identify the dynamic parameters of a six-degree-of-freedom robotic arm. This approach significantly enhances the fidelity of dynamic models, enabling more precise motion control and interaction with external environments. With 14 citations in a short time, his work is gaining traction among researchers working on robot modeling, control optimization, and industrial automation. Xiao’s contributions are particularly valuable for advancing the performance of self-designed robotic systems, where accurate parameter identification is critical for tasks ranging from assembly to collaborative operations. His research bridges theoretical optimization techniques with practical engineering challenges, making him a notable emerging voice in the field of robotic dynamics and intelligent control.
Research Focus
Key Achievements
Top Papers
- 1