Yingyi Lei
Papers
1
Total Citations
4
H-Index
1
About
Yingyi Lei is a researcher in human–robot interaction and intelligent control systems, with a focus on developing robust sensor fusion and motion estimation techniques for robotic interfaces. Their most cited work, "A human–robot interface using particle filter, Kalman filter, and over-damping method" (2016), introduces a hybrid filtering approach that integrates particle filters and Kalman filters with an over-damping mechanism to enhance the stability and accuracy of human–robot communication. This contribution addresses critical challenges in real-time motion tracking and noise reduction, laying groundwork for safer and more responsive robotic systems. While their citation count reflects an emerging presence in the field, Lei’s work demonstrates a methodical approach to bridging theoretical filtering algorithms with practical interface design. Their research holds potential implications for assistive robotics and teleoperation, where precise human intent interpretation is essential. As the field of human–robot collaboration expands, Lei’s contributions offer a foundation for further exploration in adaptive control and multi-sensor integration.
Research Focus
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Top Papers
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