REFLEX Dataset: A Multimodal Dataset of Human Reactions to Robot Failures and Explanations

This work presents REFLEX: Robotic Explanations to FaiLures and Human EXpressions, a comprehensive multimodal dataset capturing human reactions to robot failures and subsequent explanations in collaborative settings. It aims to facilitate research into human-robot interaction dynamics, addressing the need to study reactions to both initial failures and explanations, as well as the evolution of these reactions in long-term interactions. By providing rich, annotated data on human responses to different types of failures, explanation levels, and explanation varying strategies, the dataset contributes to the development of more robust, adaptive, and satisfying robotic systems capable of maintaining positive relationships with human collaborators, even during challenges like repeated failures.

Authors

Institutions

Publication Details

Published
2025-03-04
DOI
https://doi.org/10.1109/hri61500.2025.10974185
Citations
2
Primary Topic
Occupational Health and Safety Research
Type
article
Field-Weighted Citation Impact
3.08
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

REFLEX Dataset: A Multimodal Dataset of Human Reactions to Robot Failures and Explanations

Parag Khanna, Christian Smith, Elmira Yadollahi, Adil G. Naoum et al.
2 citations
Occupational Health and Safety Research
3.08
article

REFLEX Dataset: A Multimodal Dataset of Human Reactions to Robot Failures and Explanations

Parag Khanna, Christian Smith, Elmira Yadollahi, Adil G. Naoum, Mårten Björkman
article en
2 citations

Abstract

This work presents REFLEX: Robotic Explanations to FaiLures and Human EXpressions, a comprehensive multimodal dataset capturing human reactions to robot failures and subsequent explanations in collaborative settings. It aims to facilitate research into human-robot interaction dynamics, addressing the need to study reactions to both initial failures and explanations, as well as the evolution of these reactions in long-term interactions. By providing rich, annotated data on human responses to different types of failures, explanation levels, and explanation varying strategies, the dataset contributes to the development of more robust, adaptive, and satisfying robotic systems capable of maintaining positive relationships with human collaborators, even during challenges like repeated failures.

Lancaster University (GB), KTH Royal Institute of Technology (SE)
Climate action
Openalex Percentile: Top 10%
Occupational Health and Safety Research
3.08
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.