Ling Qin
Papers
1
Total Citations
2
H-Index
1
About
Ling Qin is a researcher whose work bridges intelligent control systems and robotics, with a particular focus on adaptive, bio-inspired approaches to motion and position control. Her key research areas include echo state networks, multi-agent distributed control, and humanoid robot kinematics. In her most cited work, she developed a novel framework for NAO robot joint position control using echo state networks, a reservoir computing paradigm that excels at modeling nonlinear dynamics. This approach divides the control process into two phases: sensor parameter release and dynamic coupling between angular acceleration and joint response, enabling more natural and adaptive motion in humanoid robots. While her citation count is still building, this foundational paper demonstrates her contribution to making robotic control more efficient and biologically plausible. Her work is particularly relevant for researchers exploring the intersection of machine learning and real-time robotic systems, offering a pathway toward more autonomous and responsive humanoid robots.
Research Focus
Key Achievements
Top Papers
- 1