Papers
10
Total Citations
176
H-Index
7
About
Jimin Ge is a leading researcher in robotic manufacturing and intelligent automation, with a specialized focus on robotic weld seam grinding, laser vision sensing, and adaptive process control. His work addresses one of the most demanding challenges in advanced manufacturing: achieving high-precision, consistent surface finishing in automated welding and grinding systems. Through a series of influential publications, Ge has developed innovative solutions including adaptive parameter optimization algorithms, hand-eye calibration techniques for industrial robots, and vision-guided online correction systems — collectively accumulating over 170 citations since 2021. Among his most recognized contributions is his pioneering work on laser vision-guided robotic grinding systems, which enable real-time path correction to compensate for assembly errors and thermal deformation — a persistent challenge in large-scale structural fabrication. His investigations into residual stress distribution in high-strength steel grinding and quantitative grinding depth modeling have significantly advanced understanding of surface integrity in robotic machining. More recently, Ge has expanded into deep learning applications, developing CNN-GRU-based monitoring systems for grinding wheel wear and adaptive multi-pass welding strategies. His growing body of work positions him as an emerging authority at the intersection of robotics, computer vision, and precision manufacturing engineering.
Research Focus
Key Achievements
Top Papers
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- 3Robot welding seam online grinding system based on laser vision guidance28 citations · 2021
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- 5An efficient system based on model segmentation for weld seam grinding robot18 citations · 2022
- 6A review of research on robot machining chatter11 citations · 2024
- 7Quantitative grinding depth model for robotic weld seam grinding systems11 citations · 2023
- 8Vision Sensing-Based Online Correction System for Robotic Weld Grinding7 citations · 2023
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