Kerstin Huth

Papers

Total Citations

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About

Kerstin Huth’s research lies at the intersection of social robotics, nonverbal communication, and human-robot interaction (HRI), with a particular focus on enabling robots to understand and respond to human social cues in dynamic, real-world settings. Her major contributions center on the automatic recognition of social behaviors—especially body posture and head pose—as signals for initiating, maintaining, and terminating interactions. In her most cited work (52 citations), she demonstrated that humans use these nonverbal signals to coordinate service encounters, such as ordering drinks at a bar, providing a foundational framework for robots to interpret interaction intent. Her 2013 study (23 citations) advanced this by developing a system for automatic detection of service initiation signals, tackling the challenge of enabling a bartending robot to recognize when a customer wishes to be served. Further work (17 citations) modeled interaction states from head pose in both human-human and human-robot scenarios, empirically grounding her approach in everyday, short-term service interactions. Huth’s research is notable for its applied, scenario-driven methodology, directly informing the design of socially aware robots capable of seamless, intuitive engagement in public spaces.