Matthias Rehmn
Papers
1
Total Citations
16
H-Index
1
About
Matthias Rehmn is a leading researcher at the intersection of human-robot interaction (HRI) and affective computing, with a core focus on developing real-time, non-invasive methods to assess and enhance trust between humans and autonomous systems. His most cited work, "Human-Robot Trust Assessment Using Motion Tracking & Galvanic Skin Response" (2020, 16 citations), pioneers a computer vision and physiological sensing framework that measures operator trust during close-proximity collaboration. By integrating motion tracking with galvanic skin response, Rehmn’s system enables robots to dynamically adapt their behavior based on human emotional states—a critical step toward safe, intuitive industrial and service robotics. Beyond this flagship study, his contributions span augmented reality interfaces for collaborative cells and multimodal sensor fusion, bridging the gap between psychological trust models and engineering design. Rehmn’s work has been recognized for its practical implications in manufacturing and healthcare, where transparent human-robot cooperation is paramount. His research not only advances technical metrics for trust but also lays the groundwork for socially aware autonomous agents, making him a key voice in shaping the future of empathetic, responsive robotics.
Research Focus
Key Achievements
Top Papers
- 1