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About

Thies Pfeiffer investigates the intersection of human-robot interaction (HRI) and mixed reality, focusing on how robots can seamlessly collaborate with non-expert users in everyday spaces like shopping malls and nursing homes. His core research addresses the critical challenge of bridging false expectations about robotic capabilities through intuitive communication. Pfeiffer’s major contributions include developing mixed reality techniques to improve human-robot handover tasks, with his 2018 paper on this topic garnering 10 citations. He has also pioneered the study of spatial referencing, examining how gaze and pointing gestures facilitate shared understanding between humans and robots, as detailed in his 2014 work (8 citations). Notably, his "WYSIWICD" framework (2018) tackles the problem of operator misconceptions by making robot limitations transparent. Pfeiffer further advances the field by modeling joint attention and hand-eye coordination, using automatic mapping of fixations to target objects to teach robots human-like communicative signals. His work, accumulating over 30 citations, is essential for designing accessible, trustworthy robots that can operate safely alongside people without specialized training.