Papers
2
Total Citations
5
H-Index
2
About
Qiguang Li’s research lies at the intersection of intelligent manufacturing, autonomous robotics, and precision machining. His work focuses on solving critical industrial challenges through advanced computer vision and control algorithms. In a key contribution, Li developed a novel identification and location method for strip ingots using k-means clustering and color segmentation, enabling autonomous robot systems to sort steel ingots with greater efficiency. This work, published in 2023, has already garnered 3 citations for its practical impact on industrial automation. Li also made significant strides in precision grinding technology, proposing a NURBS interpolation method for tangential point tracing grinding of eccentric shafts—critical components in industrial robot RV reducers. His 2019 paper on this topic, with 2 citations, addresses the X‑C linkage grinding model to improve machining quality. Beyond these contributions, Li’s research demonstrates a clear commitment to bridging theoretical algorithms with real-world manufacturing applications, making his work valuable for students and researchers in robotics, automation, and advanced manufacturing.
Research Focus
Key Achievements
Top Papers
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- 2