Papers

3

Total Citations

53

H-Index

3

About

Dr. Lefeng Gu is a leading researcher in the field of robotic precision and calibration, with a primary focus on enhancing the accuracy of industrial and collaborative robots through innovative kinematic modeling. His major contributions center on developing self-calibration methods that eliminate the need for expensive external metrology equipment. Notably, his 2023 work on a "local POE-based self-calibration method using position and distance constraints for collaborative robots" has garnered 44 citations, reflecting its significant impact on making high-precision calibration more accessible and practical for collaborative robot systems. Dr. Gu’s earlier research introduced a two-step self-calibration approach using portable measurement devices, while his most recent work (2025) tackles the challenging ill-posed identification issues in a 5-DoF parallel machining robot, proposing an adaptive and weighted identification method based on generalized cross-validation. This ongoing dedication to solving complex error characteristics in robotic systems—from serial industrial arms to parallel machining platforms—positions Dr. Gu as a key contributor to the advancement of robot metrology, directly supporting the deployment of robots in high-precision industrial applications like machining and assembly.

Research Focus

Key Achievements

3
H-Index
3
Papers
53
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
A local POE-based self-calibration method using position and distance constraints for collaborative robots
44 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Tsinghua University, Ningbo Institute of Industrial Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago