Papers
1
Total Citations
41
H-Index
1
About
Yaqi Mu is a leading researcher in human-robot collaboration (HRC), with a primary focus on developing data-driven models for human motion prediction. Their most-cited work, "Data Driven Models for Human Motion Prediction in Human-Robot Collaboration" (2020, 41 citations), addresses a critical challenge in HRC: enabling robots to anticipate human intentions early in motion sequences. By leveraging machine learning techniques, Mu’s research allows robots to plan safe, proactive trajectories before human movements are completed, significantly enhancing both safety and efficiency in shared workspaces. This contribution is foundational for advancing intuitive and responsive robotic systems. Mu’s work has been widely recognized for its practical impact on industrial automation and collaborative robotics, with their citation record reflecting growing influence in the field. Their achievements underscore a commitment to bridging the gap between human intent and robotic action, making them a key figure in the evolution of intelligent, human-aware automation.
Research Focus
Key Achievements
Top Papers
- 1Data Driven Models for Human Motion Prediction in Human-Robot Collaboration41 citations · 2020