Tinghui Ning
Papers
1
Total Citations
2
H-Index
1
About
Tinghui Ning is a researcher whose work lies at the intersection of robotics, neural networks, and human motion analysis. Their most-cited paper, "An on-line gait generator for bipedal walking robot based on neural networks" (2011, 2 citations), introduces an innovative approach to achieving efficient, human-like locomotion in bipedal robots. By mounting MTi sensors on human subjects to capture lower-limb kinematics, Ning developed an on-line gait synthesis scheme that integrates real-time angular data from hip and knee joints into neural network-driven control. This work contributes to the broader challenge of enabling robots to walk with natural, adaptive gaits, bridging the gap between biological motion and robotic actuation. While their citation count is modest, Ning’s focus on sensor-based, bio-inspired control highlights a commitment to practical, data-driven robotics. Their research is particularly relevant for students and engineers exploring neural network applications in real-time robotic systems, offering a foundation for further advances in autonomous walking and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1