Qingxue Huang
Papers
3
Total Citations
8
H-Index
2
About
Qingxue Huang is a researcher advancing the frontiers of robotic manipulation and intelligent manufacturing, with a focus on bionic design, kinematics, and machine vision. His work centers on developing high-precision, efficient robotic systems for industrial applications, particularly in grinding and finishing processes. Huang’s major contributions include the configuration design of a bionic grinding manipulator inspired by the human upper limb, which enhances dexterity and adaptability in automated tasks. He has also pioneered a deep neural network (DNN) method for fast, accurate prediction of kinematics solutions in steel bar grinding robots, enabling real-time online operations. Additionally, Huang developed an automatic calibration technique for quadruped robots, combining machine vision and artificial neural networks to correct leg joint angles and improve positional accuracy—a critical step for motion stability. While his most-cited papers (each garnering 2–3 citations) are early in their impact trajectory, they represent foundational work in bridging simulation and practical robotics. Huang’s research is notable for its integration of bionics, AI, and automation, offering scalable solutions for precision manufacturing and autonomous systems.
Research Focus
Key Achievements
Top Papers
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