Person Transfer in the Field: Examining Real World Sequential Human-Robot Interaction Between Two Robots
Tan, Xiang Zhi, Carter, Elizabeth J., Steinfeld, Aaron
–arXiv.org Artificial Intelligence
With more robots being deployed in the world, users will likely interact with multiple robots sequentially when receiving services. In this paper, we describe an exploratory field study in which unsuspecting participants experienced a ``person transfer'' -- a scenario in which they first interacted with one stationary robot before another mobile robot joined to complete the interaction. In our 7-hour study spanning 4 days, we recorded 18 instances of person transfers with 40+ individuals. We also interviewed 11 participants after the interaction to further understand their experience. We used the recorded video and interview data to extract interesting insights about in-the-field sequential human-robot interaction, such as mobile robot handovers, trust in person transfer, and the importance of the robots' positions. Our findings expose pitfalls and present important factors to consider when designing sequential human-robot interaction.
arXiv.org Artificial Intelligence
Jun-10-2024
- Country:
- North America > United States > Pennsylvania > Allegheny County > Pittsburgh (0.14)
- Genre:
- Research Report > New Finding (0.48)
- Industry:
- Health & Medicine (0.47)
- Technology:
- Information Technology > Artificial Intelligence > Robots
- Humanoid Robots (0.93)
- Locomotion (0.61)
- Information Technology > Artificial Intelligence > Robots