Andrea Ruo
Papers
6
Total Citations
36
H-Index
4
About
Andrea Ruo is at the forefront of human-robot collaboration (HRC) research, with a focus on making industrial robots safer and more intuitive for human operators. Her key research areas include multimodal stress assessment, mental workload evaluation, and socially responsible robot navigation. Ruo’s major contributions lie in developing novel frameworks that integrate physiological signals—such as EEG and other biometric data—to quantify operator stress and cognitive load during collaborative tasks. Her most cited work, “Assessing operator stress in collaborative robotics: A multimodal approach” (2024, 19 citations), introduces a pioneering method for real-time stress detection, directly addressing trust and discomfort issues in Industry 4.0 environments. She also created the SenseCobot dataset, a multimodal resource capturing operator physiological responses during HRC programming tasks. Additionally, Ruo has advanced robot navigation by applying Control Barrier Functions (CBF) and Signal Temporal Logic (STL) to ensure socially responsible movement in crowded spaces, as seen in her 2024 papers on motion planning. Her work bridges cognitive science and control engineering, offering practical solutions for safer, more adaptive human-robot teams.
Research Focus
Key Achievements
Top Papers
- 1Assessing operator stress in collaborative robotics: A multimodal approach19 citations · 2024
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