Papers
5
Total Citations
21
H-Index
3
About
Yanzheng Li is a leading researcher in intelligent robotics and manufacturing, specializing in multi-robot coordination, point cloud processing, and process simulation for industrial automation. His work addresses critical challenges in large-scale dimensional inspection, robotic quality measurement, and welding task planning. Li’s most cited paper, “Multi-robot coverage path planning for dimensional inspection of large free-form surfaces based on hierarchical optimization” (2023, 11 citations), introduces a novel hierarchical approach that optimizes coverage efficiency for complex geometries, significantly advancing automated inspection in aerospace and automotive industries. His subsequent contributions, including “GeoContrast: Geometric knowledge-based contrast learning for industrial point cloud segmentation” (2025, 4 citations) and “A Two-Stage Trajectory Planning Method for Online Robotic Quality Measurement” (2024, 3 citations), demonstrate his focus on integrating geometric knowledge with deep learning to enhance semantic understanding and real-time adaptability in unstructured environments. Li’s research on nonrigid point cloud registration for robot calibration and time-energy optimization for multi-robot welding further underscores his impact on improving operational accuracy and efficiency. With a growing citation record and a clear trajectory toward high-fidelity digital twin applications, Yanzheng Li is shaping the future of smart manufacturing and robotic process simulation.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5