Roland Buchner
Papers
12
Total Citations
297
H-Index
8
About
Roland Buchner is a researcher whose work sits at the intersection of human-robot interaction (HRI), user experience, and social signal processing. His research has made significant contributions to understanding how humans and robots communicate, particularly in challenging real-world and industrial settings. Buchner's most influential work focuses on the social dynamics of error situations in HRI. His 2015 systematic video analysis of human social signals during robot errors — now with 96 citations — provided the field with a crucial framework for helping robots recognize and respond to breakdowns in interaction. Complementing this, his investigation into how robot actions affect reaction times in error scenarios further deepened understanding of human behavioral responses in HRI. Beyond error analysis, Buchner has made notable methodological contributions, including a widely cited Wizard of Oz evaluation framework (55 citations) that has helped researchers assess user experience without requiring fully autonomous systems. His longitudinal work on how user experience evolves over time — studied in both public spaces and semiconductor manufacturing cleanrooms — demonstrates a rare commitment to ecologically valid, applied research. With over 290 total citations, Buchner's body of work bridges academic HRI research and industrial practice, making him a valuable voice for researchers and practitioners seeking to design more human-centered robotic systems.
Research Focus
Key Achievements
Top Papers
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- 6User experience of industrial robots over time21 citations · 2012
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- 10Development of a context model based on video analysis4 citations · 2011