Papers
2
Total Citations
22
H-Index
2
About
Pu Zheng’s research lies at the critical intersection of human-robot collaboration, motion planning, and industrial safety—core pillars of the Industry 4.0 paradigm. Her work addresses the pressing challenge of enabling close, efficient human-robot interaction without compromising safety. Zheng’s major contribution is the development of online, optimal motion generation algorithms that guarantee safety in shared workspaces. Her most cited paper (2022, 15 citations) proposes a novel method for predicting human arm motion to enable proactive collision avoidance, transforming robots from reactive machines into intelligent partners. A second influential work (2020, 7 citations) demonstrates that even at speeds up to 2 m/s, serious injury risk remains low (5%), yet she argues that collisions should be avoided entirely—a principle that drives her design of robust, real-time safety frameworks. By equipping robots with exteroceptive sensing and predictive capabilities, Zheng is pioneering a future where humans and robots work side-by-side seamlessly. Her achievements are particularly notable for advancing both the theoretical foundations and practical implementations of safe, human-centric automation, making her a rising voice in collaborative robotics.
Research Focus
Key Achievements
Top Papers
- 1Human Arm Motion Prediction for Collision Avoidance in a Shared Workspace15 citations · 2022
- 2