Observations of atypical users from a pilot deployment of a public-space social robot in a church
August 14, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Andrew Blair, Peggy Gregory, Mary Ellen Foster
arXiv ID
2508.16622
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.RO
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Though a goal of HRI is the natural integration of social robots into everyday public spaces, real-world studies still occur mostly within controlled environments with predetermined participants. True public spaces present an environment which is largely unconstrained and unpredictable, frequented by a diverse range of people whose goals can often conflict with those of the robot. When combined with the general unfamiliarity most people have with social robots, this leads to unexpected human-robot interactions in these public spaces that are rarely discussed or detected in other contexts. In this paper, we describe atypical users we observed interacting with our robot, and those who did not, during a three-day pilot deployment within a large working church and visitor attraction. We then discuss theoretical future advances in the field that could address these challenges, as well as immediate practical mitigations and strategies to help improve public space human-robot interactions in the present. This work contributes empirical insights into the dynamics of human-robot interaction in public environments and offers actionable guidance for more effective future deployments for social robot designers.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted