Shujun Chen

Papers

Total Citations

H-Index

About

Shujun Chen is an emerging researcher specializing in industrial robotics, with a particular focus on kinematic calibration, parameter identification, and measurement precision for multi-joint robotic systems. His work addresses a critical challenge in modern manufacturing: improving the positional accuracy of industrial robots through rigorous mathematical modeling and systematic error analysis. Chen's most notable contribution, "Investigation of axis-fitting-based measurement and identification techniques for kinematic parameters in multi-joint industrial robots" (2024), has already accumulated 10 citations, a strong indicator of early impact in a competitive field. This work advances axis-fitting methodologies to more reliably extract and identify kinematic parameters across complex robotic configurations. Building on this foundation, his 2025 study introduces a multi-error source model paired with an optimized measurement pose selection strategy, directly tackling the long-standing problem of incomplete error modeling in kinematic identification — a gap that significantly limits real-world robot accuracy. Together, these contributions position Chen as a researcher committed to bridging theoretical rigor with practical industrial application. His work holds meaningful implications for robotics engineers and manufacturers seeking tighter tolerances and more reliable automated systems, making him a researcher to watch as his career develops.