Shoujie He

China University of Petroleum, Beijing, The University of Osaka

Papers

Total Citations

H-Index

About

Shoujie He’s research bridges robotics, non-destructive testing, and intelligent automation, with a focus on developing systems that perceive and interact with physical environments. His most cited work introduces a magnetic crawler climbing detection robot that leverages metal magnetic memory testing technology—a novel approach for inspecting ferromagnetic structures without contact. This robot, designed to navigate vertical and inverted surfaces, enables early detection of stress concentration and micro-damage in industrial equipment, offering a safer, more efficient alternative to manual inspection. With 67 citations, this paper highlights He’s contribution to advancing robotic inspection in hazardous environments. Earlier in his career, He explored machine understanding of visual diagrams, publishing a system that interprets illustrations in assembly manuals. This foundational work, though less cited, aimed to equip robots with the ability to parse sequential, diagrammatic instructions for automated assembly—a precursor to modern vision-guided robotics. He’s research thus spans from practical, field-deployable inspection robots to conceptual frameworks for robotic reasoning, demonstrating a sustained commitment to integrating perception, mobility, and automation in engineering systems.