Weixing Qian
Papers
4
Total Citations
30
H-Index
2
About
Weixing Qian is a leading researcher in the fields of pedestrian navigation, inertial navigation systems, and autonomous robotics, with a particular focus on humanoid and exoskeleton platforms. His work bridges machine learning and sensor fusion to solve critical challenges in robot localization and gait analysis. Qian’s most influential contribution is a pedestrian navigation method that leverages machine learning and gait feature assistance, which has garnered 14 citations and addresses the pressing need for robust navigation in humanoid robots. He further advanced the field with a LiDAR–inertial SLAM approach that mitigates degeneracy in feature-poor environments, earning 13 citations and demonstrating his ability to enhance robot mapping and localization reliability. His research also extends to exoskeleton robots, where he developed a gait recognition and autonomous location method using support vector machines, and to miniature quadruped robots, introducing a zero-velocity update-aided navigation technique with an adapted virtual inertial measurement unit. Qian’s work is notable for its practical impact on improving the autonomy and accuracy of robotic systems in complex, real-world environments, making him a key figure in advancing navigation technology for next-generation robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2A LiDAR–Inertial SLAM Method Based on Virtual Inertial Navigation System13 citations · 2023
- 3
- 4