Pei Jia

Beijing Research Institute of Automation for Machinery Industry (China)

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About

Pei Jia is a researcher whose work spans robotics, control systems, and intelligent inspection technologies. With contributions bridging classical control theory and modern deep learning applications, Jia has established a meaningful footprint in two distinct but complementary domains. In the field of robotics control, Jia's 2008 work introduced a robust decentralized trajectory tracking control method for robot manipulators, leveraging extended state observers to estimate unknown dynamics and external disturbances. By deploying multiple parallel extended state observers, this approach elegantly addressed model uncertainty without requiring precise system modeling — a significant practical advancement for real-world robotic applications, earning 7 citations. More recently, Jia has turned attention toward intelligent visual inspection systems, proposing a two-step pointer meter recognition method based on the YOLOv7 architecture. This work addresses critical safety challenges in chemical plant environments, enabling explosion-proof inspection robots to autonomously read analog meters in hazardous areas where manual inspection poses serious risks — garnering 3 citations since its 2023 publication. Together, these contributions reflect a cohesive research vision: making robotic systems more autonomous, reliable, and capable of operating safely in demanding real-world environments. Students interested in robotics, control engineering, or industrial AI applications will find Jia's work both technically rigorous and practically motivated.