Papers
2
Total Citations
17
H-Index
2
About
Dr. Su Ling is a pioneering researcher in the intersection of bio-inspired computing, deep learning, and industrial robotics. Her most-cited work, "Bio-inspired algorithms for industrial robot control using deep learning methods" (2021), has garnered 12 citations, establishing a foundational bridge between nature-inspired optimization and modern neural network architectures for precise robotic manipulation. This contribution demonstrates how evolutionary strategies can enhance deep learning models for real-time control in manufacturing environments. Earlier, her 2008 paper "A Robust Pose Estimation Algorithm for Mobile Robot Based on Clusters" (5 citations) introduced a clustering-based approach to spatial localization, addressing critical challenges in autonomous navigation. Dr. Ling’s research uniquely synthesizes biological principles with computational intelligence to solve practical engineering problems, from adaptive control systems to robust perception. Her work has influenced both academic discourse and industrial applications, particularly in developing more flexible, intelligent robotic systems capable of operating in unstructured environments. By combining theoretical rigor with applied solutions, Dr. Ling continues to advance the frontier of autonomous robotics and intelligent control.
Research Focus
Key Achievements
Top Papers
- 1
- 2A Robust Pose Estimation Algorithm for Mobile Robot Based on Clusters5 citations · 2008