One Robot, Many Minds: Factors Shaping Visitors' Evaluation of an Autonomous Museum Robot Guide

Robots are no longer just tools—they are becoming social agents that can shape how we engage with culture. This study examines what influences visitors’ perceptions of an autonomous museum guide robot, focusing not only on technical capabilities but also on human-centered factors. In a maritime exhibition, 34 participants interacted with a fully autonomous, LLM-powered robot acting as a museum guide. Using self-report questionnaires, we explored how individual differences - age and prior experience with robots — interacted with experimental conditions to shape participants’ impressions of the robot. Our findings suggest that these personal factors significantly affect how visitors evaluate the robot, suggesting that effective design must reflect the diversity of users’ experiences and expectations. By acknowledging the complexity of human-robot interaction, we move closer to creating robotic guides that are not only functional but also socially attuned.

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Publication Details

Published
2025-11-10
DOI
https://doi.org/10.1145/3765766.3765777
Citations
2
Primary Topic
Social Robot Interaction and HRI
Type
article
Field-Weighted Citation Impact
4.88
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article

One Robot, Many Minds: Factors Shaping Visitors' Evaluation of an Autonomous Museum Robot Guide

Alessandra Sciutti, Francesco Rea, Manuel G. Catalano, Luca Garello et al.
2 citations
Social Robot Interaction and HRI
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article

One Robot, Many Minds: Factors Shaping Visitors' Evaluation of an Autonomous Museum Robot Guide

Alessandra Sciutti, Francesco Rea, Manuel G. Catalano, Luca Garello, Francesca Cocchella
article en
2 citations

Abstract

Robots are no longer just tools—they are becoming social agents that can shape how we engage with culture. This study examines what influences visitors’ perceptions of an autonomous museum guide robot, focusing not only on technical capabilities but also on human-centered factors. In a maritime exhibition, 34 participants interacted with a fully autonomous, LLM-powered robot acting as a museum guide. Using self-report questionnaires, we explored how individual differences - age and prior experience with robots — interacted with experimental conditions to shape participants’ impressions of the robot. Our findings suggest that these personal factors significantly affect how visitors evaluate the robot, suggesting that effective design must reflect the diversity of users’ experiences and expectations. By acknowledging the complexity of human-robot interaction, we move closer to creating robotic guides that are not only functional but also socially attuned.

Italian Institute of Technology (IT)
Openalex Percentile: Top 4%
Social Robot Interaction and HRI
4.88
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