Papers
10
Total Citations
129
H-Index
6
About
Ziyang Xie is an emerging researcher whose work sits at the intersection of human-robot collaboration (HRC), occupational safety, and intelligent robotics. His research addresses two critical dimensions of modern industrial environments: the psychological wellbeing of workers and the prevention of physical injuries during collaborative robot tasks. Xie's most cited work—a 2022 review on mental stress and safety awareness in HRC (66 citations)—established a foundational framework for understanding how robotic systems affect human psychology. Building on this, he has systematically investigated how factors such as robot speed, trajectory, and approach direction influence workers' mental stress during handover tasks, translating laboratory findings into actionable design principles for safer human-robot interactions. Equally notable is his contribution to musculoskeletal disorder prevention. Through reinforcement learning and conditional variational auto-encoder models, Xie has developed intelligent methods that optimize worker postures in real time, reducing injury risks without relying on predefined robot models. His collision avoidance research further demonstrates his commitment to physical safety, employing computer vision to proactively protect workers from hazardous robot contacts. More recently, his Vid2Sim project (2025, 7 citations) signals an exciting expansion into simulation-based robot learning for urban navigation, reflecting a researcher of broad and growing ambition.
Research Focus
Key Achievements
Top Papers
- 1Mental stress and safety awareness during human-robot collaboration - Review66 citations · 2022
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- 10A human-robot collision avoidance method using a single camera3 citations · 2022