Jie Lei
Papers
1
Total Citations
54
H-Index
1
About
Jie Lei is a researcher whose work lies at the intersection of robotics and computer vision, with a particular focus on enabling humanoid robots to learn and replicate human motion. His most cited paper, "Whole-body humanoid robot imitation with pose similarity evaluation" (2014, 54 citations), introduces a novel framework for real-time imitation learning. In this work, Lei developed a method for a humanoid robot to observe a human demonstrator and accurately mimic whole-body poses, incorporating a pose similarity evaluation metric that ensures both kinematic accuracy and stability. This contribution is significant because it addresses a core challenge in human-robot interaction: how to transfer complex, dynamic human movements to robots in a way that is both natural and physically feasible. By bridging the gap between human motion capture and robotic control, Lei's research has implications for assistive robotics, entertainment, and rehabilitation. His work demonstrates a clear impact in the field, as evidenced by the sustained citations to his 2014 paper, which remains a reference point for researchers exploring imitation learning and humanoid control.
Research Focus
Key Achievements
Top Papers
- 1Whole-body humanoid robot imitation with pose similarity evaluation54 citations · 2014