Stefan Jehring

Papers

Total Citations

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About

Stefan Jehring’s research lies at the intersection of human-robot interaction and gesture-based control, with a particular focus on enabling intuitive, non-verbal communication between humans and mobile robots. His most cited work, “Detecting Deictic Gestures for Control of Mobile Robots” (2016), introduces a framework for recognizing pointing and referencing gestures in real time, allowing robots to interpret natural human cues for navigation and task execution. This contribution is foundational for developing more responsive and user-friendly robotic systems in collaborative environments. Although his citation count remains modest, Jehring’s work is notable for its practical emphasis on real-world deployment, bridging the gap between computer vision, machine learning, and robotics. His research has implications for assistive technologies, industrial automation, and autonomous systems where seamless human-robot cooperation is critical. Jehring’s approach underscores the importance of designing robots that understand not just commands, but the spatial and contextual intent behind human gestures, making his contributions a stepping stone for future advances in intuitive robotic control.