Ziqiang Zhang

Papers

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About

Ziqiang Zhang is an emerging researcher specializing in industrial robotics, with a focused expertise in robotic calibration methodologies and kinematic parameter identification. His work addresses a critical challenge in modern manufacturing and automation: improving the positional accuracy of industrial robots through more comprehensive and systematic error modeling approaches. His most notable contribution, published in 2025, introduces an innovative calibration method that tackles the longstanding problem of incomplete error source consideration in kinematic parameter identification models. By developing a multi-error source model combined with an optimized measurement pose selection strategy, Zhang's research offers a more rigorous framework for enhancing robot precision — a factor of paramount importance in high-stakes applications such as aerospace manufacturing, medical robotics, and precision assembly. Though early in his citation trajectory with work still gaining traction in the research community, his approach to systematically optimizing measurement configurations represents a meaningful methodological advancement in robot calibration science. Students and engineers working in robot accuracy improvement, manufacturing automation, or mechatronics will find Zhang's contributions particularly relevant as the demand for ultra-precise robotic systems continues to grow across advanced industries.