Papers
2
Total Citations
8
H-Index
2
About
Dr. Jigang Wu is a leading researcher in intelligent robotic manufacturing, with a primary focus on adaptive welding and grinding process optimization. His work addresses critical challenges in large-scale steel fabrication, particularly the complexities of robotic multi-layer multi-pass (MLMP) welding for medium-thick plates. In a highly cited 2025 study, Dr. Wu introduced an adaptive path and process planning method that compensates for clamping errors and continuous thermal deformation—common issues in heavy industrial structures—enabling more universal, efficient, and high-quality robotic welding without manual intervention. Complementing this, he developed an innovative online monitoring approach for grinding wheel wear during robotic weld grinding, employing an enhanced CNN-GRU deep learning model. This work, also from 2025, has already garnered 6 citations, underscoring its immediate impact on predictive maintenance and process control. By integrating real-time sensing with adaptive planning, Dr. Wu’s contributions are advancing the autonomy and reliability of robotic systems in demanding manufacturing environments. His research is pivotal for industries seeking to automate complex welding and finishing tasks, reducing waste and improving structural integrity.
Research Focus
Key Achievements
Top Papers
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