Qingzhi Ji
Papers
4
Total Citations
56
H-Index
4
About
Qingzhi Ji is a researcher at the forefront of intelligent robotic machining, specializing in the precision processing of stone materials. His work centers on the critical challenge of enhancing the accuracy and surface quality of robotic manipulators for complex, high-value stone products. Ji’s major contributions include developing a novel machining error prediction and compensation technology for stone-carving robots, a foundational study that has garnered 32 citations. He has further advanced the field by proposing an adaptive terminal sliding mode controller, integrated with a radial basis function neural network, to improve robotic manipulator control. Demonstrating a data-driven approach, Ji has applied an improved whale optimization algorithm to support vector regression (IWOA-SVR) for accurately predicting surface roughness during robotic grinding, a method detailed in his 2022 paper. His research also explores the influence of machining trajectory on grinding force for complex-shaped stone. With a growing citation record that underscores the practical relevance of his work, Ji is establishing himself as a key contributor to the automation and precision of stone manufacturing, bridging the gap between robotics and traditional craftsmanship.
Research Focus
Key Achievements
Top Papers
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