Publication

Adapting explanations’ level of detail in a longitudinal in-the-wild office delivery robot: Ongoing results

Conference Article

Conference

ACM/IEEE International Conference on Human-Robot Interaction (HRI)

Edition

2026

Doc link

https://scholar.google.com/citations?view_op=view_citation&hl=ca&user=YOTeAXUAAAAJ&citation_for_view=YOTeAXUAAAAJ:LkGwnXOMwfcC

File

Download the digital copy of the doc pdf document

Authors

Abstract

We present an ongoing longitudinal in-the-wild study of an office delivery robot that adapts the level of detail of its explanations to users of failure or unexpected events. We compare three explanation strategies: minimal “what happened” explanations, fully detailed including “what + why” reasons, and a personalised variant that tailors detail based on tracked user knowledge. Additionally, some users can request on‑demand extra follow-up explanations. Ongoing results from the first two weeks indicate that personalised explanations preserve both subjective and objective understanding while providing a level of detail closer to correct when compared to fully detailed explanations. Moreover, users who receive personalised explanations request fewer extra follow-up explanations compared to the group receiving minimal explanations. Full study results will confirm these results and provide their evolution through the next 2 weeks of deployment.

Categories

intelligent robots, service robots, social aspects of automation.

Author keywords

Explainable Human-Robot Interaction, Longitudinal in-the-wild studies

Scientific reference

F. Gebelli, A. Garrell Zulueta, S. Lemaignan and R. Ros. Adapting explanations’ level of detail in a longitudinal in-the-wild office delivery robot: Ongoing results, 2026 ACM/IEEE International Conference on Human-Robot Interaction, 2026, Edinburgh, Scotland, UK, ACM/IEEE.