Paul Schweidler

About

Paul Schweidler investigates how pseudo-social cues—specifically, robot eyes—can enhance human-robot interaction (HRI) by leveraging innate human attentional mechanisms. His core research explores whether robot gaze can function like human gaze to intuitively direct attention, improve task performance, and build trust in collaborative settings. In his most cited work, "Humans Can’t Resist Robot Eyes – Reflexive Cueing With Pseudo-Social Stimuli" (14 citations), he demonstrates that robot eyes trigger reflexive attentional shifts similar to human social cues. His 2023 study on predictive robot eyes in industrial cooperation tasks (7 citations) shows these cues boost trust and efficiency. Schweidler also advances HRI methodology, comparing virtual reality, screen-based, and real-world settings (11 citations) to validate cost-effective experimental approaches. With a growing body of work (over 47 total citations), his findings have practical implications for designing more intuitive and trustworthy collaborative robots in manufacturing and service contexts.

Research Focus

Key Achievements

Top Papers

1. 1
   Humans Can’t Resist Robot Eyes – Reflexive Cueing With Pseudo-Social Stimuli

   14 citations · 2022
2. 2
   The potential of robot eyes as predictive cues in HRI—an eye-tracking study

   12 citations · 2023
3. 3
   Virtual reality check: a comparison of virtual reality, screen-based, and real world settings as research methods for HRI

   11 citations · 2023
4. 4
   Effects of Predictive Robot Eyes on Trust and Task Performance in an Industrial Cooperation Task

   7 citations · 2023
5. 5
   Effects of predictive robot eyes on attentional processes in HRI

   3 citations · 2022

Key Collaborators

Contact & Links