Gerald Stollnberger

University of Salzburg

Papers

19

Total Citations

678

H-Index

12

About

Gerald Stollnberger is a human-robot interaction (HRI) researcher whose work spans robot error handling, social signal processing, robot humor, and applied robotics in medical and industrial contexts. His most influential contribution examines how humans perceive and respond to faulty robots — a 2017 study titled "To Err Is Robot" has accumulated 236 citations, establishing him as a leading voice on error dynamics in HRI. Building on this, Stollnberger developed methods for automatically detecting error situations through head and shoulder movement classification, and conducted systematic video analyses of social signals humans exhibit during robot failures, demonstrating that these overlooked moments carry significant research value. Beyond error research, Stollnberger has made notable contributions to robot humor, exploring how self-irony and Schadenfreude affect perceived robot likability, and to autonomous vehicle-pedestrian communication, drawing on social robotics principles to inform safer street interactions. His applied work includes user-centred design of a tele-operated echocardiography robot and augmented reality tools for industrial robot programming. Across his portfolio, Stollnberger consistently bridges theoretical HRI inquiry with real-world usability, making his research highly relevant to both academic audiences and practitioners developing socially intelligent, human-compatible robotic systems.

Research Focus

Key Achievements

12
H-Index
19
Papers
678
Total Citations
36
Avg Citations/Paper
🏆 Most Cited Paper
To Err Is Robot: How Humans Assess and Act toward an Erroneous Social Robot
236 citations · 2017
📈 Most Prolific Year: 2017 (6 Papers)
🤝 Key Collaborators: 34
🏛 Institutions: University of Salzburg

Top Papers

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    Elements of Humor
    19 citations · 2017
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Key Collaborators

Contact & Links

Available for collaboration
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