Yuxuan Cai
Papers
1
Total Citations
8
H-Index
1
About
Yuxuan Cai is a researcher at the forefront of intelligent manufacturing and robotic safety, with a focus on collision detection and classification in smart factory environments. Their most-cited work, "Robot Collisions Classification Based on Variational Mode Decomposition of Vibration Measurements" (2024, 8 citations), introduces a novel method that leverages motor current and robot link vibration data to classify collisions—distinguishing between different materials, impacted robot components, and whether a human is involved. This contribution is pivotal for advancing human-robot collaboration and workplace safety in Industry 4.0 settings. By applying variational mode decomposition to vibration signals, Cai’s work enables more nuanced and automated responses to robotic incidents, reducing downtime and preventing injuries. Though early in their career, Cai’s research has already garnered attention for its practical implications in real-time monitoring and adaptive control systems. Their work stands out for bridging signal processing, robotics, and safety engineering, offering a scalable solution for future factories where robots and humans work side by side.
Research Focus
Key Achievements
Top Papers
- 1