Hongdi Liu
Papers
7
Total Citations
71
H-Index
5
About
Hongdi Liu is a rising researcher in intelligent robotic machining, with a focus on vision-guided systems and precision manufacturing. His work centers on developing advanced algorithms for robotic deburring, multi-camera calibration, and real-time pose correction, particularly for complex industrial tasks like machining large irregular components. Liu’s notable contributions include a novel trajectory planning method for robotic deburring of automotive castings using adaptive weights (20 citations) and a convergent binocular vision algorithm for guiding machining robots under extended imaging dynamic range (17 citations). He also introduced GWM-view, a gradient-weighted multi-view calibration method for machining robot positioning (16 citations), and a hand-eye calibration algorithm based on multi-pixel 3D geometric centroid relocalization, which improves accuracy by addressing parameter constraints in binocular stereo vision systems. His recent work on multi-camera joint calibration considers ambient light and error uncertainty (6 citations), while his human-inspired posture optimization via multi-redundant DOFs (2025) tackles machining feasibility for large irregular components. With over 70 total citations and a growing portfolio of impactful studies, Liu is advancing the precision and adaptability of robotic manufacturing, making significant strides toward fully autonomous, vision-guided industrial robots.
Research Focus
Key Achievements
Top Papers
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