LI Wei-hua
Papers
2
Total Citations
9
H-Index
2
About
Li Wei-hua is a rising figure in robotics research, with a focus on intelligent path planning and precision modeling for industrial and service robots. His work addresses critical challenges in autonomous navigation and robotic control. In a notable 2025 study, he developed a full coverage path planning strategy for cleaning robots operating in semi-structured outdoor environments, earning 6 citations for its practical approach to complex terrain navigation. Earlier, in 2024, he pioneered a neural network–based transfer learning method to improve stiffness modeling of industrial robots using only small experimental data sets. This work, cited 3 times, overcomes the limitations of traditional virtual joint modeling (VJM) by enhancing control accuracy under dynamic loads. Li’s contributions bridge the gap between simulation and real-world performance, offering scalable solutions for both autonomous cleaning and precision manufacturing. His research demonstrates a strong commitment to advancing robotic adaptability and efficiency, making him a promising voice in modern robotics engineering.
Research Focus
Key Achievements
Top Papers
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- 2