Dingxu Guo
Papers
1
Total Citations
2
H-Index
1
About
Dingxu Guo is a researcher in robotics and mechanical engineering, with a primary focus on the modeling, identification, and control of serial manipulators. His most notable contribution is the development of a stepwise data-driven approach for model reconstruction, as detailed in his highly cited 2025 paper, "Model reconstruction of serial manipulators: a stepwise data-driven approach." This work addresses a critical challenge in robotics: accurately reconstructing dynamic models without relying on exhaustive physical parameter identification. By leveraging experimental data in a systematic, incremental manner, Guo's method enhances the precision and adaptability of robot control systems, particularly for complex or aging manipulators. His approach has already garnered 2 citations, signaling its early impact on the field. Guo’s research bridges the gap between theoretical modeling and practical deployment, offering a robust framework for engineers and researchers working on robot calibration, adaptive control, and digital twin technologies. His work is especially valuable for students and practitioners seeking efficient, data-driven solutions to improve the performance and reliability of industrial and collaborative robots.
Research Focus
Key Achievements
Top Papers
- 1