Shenghua Ye
Papers
16
Total Citations
342
H-Index
7
About
Shenghua Ye is a prominent researcher specializing in robotic metrology, industrial measurement systems, and robot calibration — fields that sit at the intersection of precision engineering and intelligent manufacturing. His work has fundamentally advanced how industrial robots are deployed for high-accuracy inspection and measurement tasks, particularly in demanding environments like automotive manufacturing. Ye's most celebrated contribution is his development of an integrated 3D scanning system for large-scale metrology (2014, 115 citations), which set new benchmarks for measurement accuracy at industrial scales. Complementing this, his vision-based self-calibration method for robotic visual inspection systems (2013, 57 citations) offered a practical breakthrough by eliminating the need for costly external apparatus, enabling field-ready kinematic error correction using only an end-effector-mounted visual sensor. His multilevel calibration technique for robots with parallelogram mechanisms (2015, 68 citations) further demonstrated his ability to tackle complex mechanical configurations. Across his career, Ye has also addressed real-world challenges such as thermal error compensation and tool center point recovery, ensuring robustness in operational conditions. With over 330 cumulative citations, his research has meaningfully shaped modern flexible coordinate measurement and robotic inspection practices, providing both theoretical rigor and practical solutions for next-generation smart factories.
Research Focus
Key Achievements
Top Papers
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- 3A Vision-Based Self-Calibration Method for Robotic Visual Inspection Systems57 citations · 2013
- 4A novel TCF calibration method for robotic visual measurement system30 citations · 2014
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- 6Measurement Robot Calibration Model and Algorithm Based on Distance Accuracy16 citations · 2008
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- 10METHOD OF ROBOT CALIBRATION BASED ON LASER TRACKER3 citations · 2007