Peek into the `White-Box': A Field Study on Bystander Engagement with Urban Robot Uncertainty

要旨

Uncertainty inherently exists in the autonomous decision-making process of robots. Involving humans in resolving this uncertainty not only helps robots mitigate it but is also crucial for improving human-robot interactions. However, in public urban spaces filled with unpredictability, robots often face heightened uncertainty without direct human collaborators. This study investigates how robots can engage bystanders for assistance in public spaces when encountering uncertainty and examines how these interactions impact bystanders' perceptions and attitudes towards robots. We designed and tested a speculative `peephole' concept that engages bystanders in resolving urban robot uncertainty. Our design is guided by considerations of non-intrusiveness and eliciting initiative in an implicit manner, considering bystanders' unique role as non-obligated participants in relation to urban robots. Drawing from field study findings, we highlight the potential of involving bystanders to mitigate urban robots' technological imperfections to both address operational challenges and foster public acceptance of urban robots. Furthermore, we offer design implications to encourage bystanders' involvement in mitigating the imperfections.

著者
Xinyan Yu
School of Architecture, Design and Planning, The University of Sydney, Sydney, NSW, Australia
Marius Hoggenmüller
School of Architecture, Design and Planning, The University of Sydney, Sydney, NSW, Australia
Tram Thi Minh. Tran
School of Architecture, Design and Planning, The University of Sydney, Sydney, NSW, Australia
Yiyuan Wang
The University of Sydney, Sydney, Australia
Qiuming Zhang
The University of Sydney, Sydney, NSW, Australia
Martin Tomitsch
University of Technology Sydney, Sydney, NSW, Australia
DOI

10.1145/3706598.3713790

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713790

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Mobile Robots

G304
5 件の発表
2025-04-28 23:10:00
2025-04-29 00:40:00
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