Fangfang Hua

Nanjing University of Aeronautics and Astronautics

Papers

Total Citations

202

H-Index

About

Dr. Fangfang Hua is a leading researcher in robotics and intelligent manufacturing, with a primary focus on enhancing the precision of industrial robots through advanced computational methods. Her major contributions center on developing novel error compensation techniques that bridge the gap between theoretical robot models and real-world performance. Dr. Hua’s most influential work, “Positioning error compensation of an industrial robot using neural networks and experimental study” (2021), has garnered 180 citations, establishing a foundational approach for using neural networks to correct kinematic inaccuracies. She further advanced this field with “Robot Positioning Error Compensation Method Based on Deep Neural Network” (2020, 22 citations), which introduced deep learning architectures to tackle the persistent challenge of low absolute positioning accuracy in high-precision manufacturing. Her research is pivotal for expanding the use of robots in industries like aerospace and automotive, where micron-level accuracy is critical. Dr. Hua’s work not only demonstrates the practical application of AI in robotics but also provides a scalable framework for improving automation reliability, making her a key figure in the evolution of intelligent manufacturing systems.