Inducing Social Perceptions of a Mobile Robot for Human-Aware Navigation

Human-aware navigation and Social Navigation are growing fields of robotics, attempting to tackle challenging navigation problems in human environments. One difficult aspect is understanding how a mobile robot's navigation behavior impacts the way they are perceived by humans, and how they interact together. In our previous work, we proposed an adaptable navigation architecture. In this paper, we describe how we determine which motion variables should be controlled by our architecture. We take a bottom-up approach by determining which primitive notions of locomotion and appearance have the most impact on people's perceptions of a mobile robot. We present the results of two online and one in-person experiment showing that the manner in which a mobile robot navigates has a significant impact on people's attribution of attitudes and physical properties to the robot.

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Publication Details

Published
2024-12-12
DOI
https://doi.org/10.1109/icarcv63323.2024.10821677
Citations
1
Primary Topic
Social Robot Interaction and HRI
Type
article
Field-Weighted Citation Impact
0.64
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article

Inducing Social Perceptions of a Mobile Robot for Human-Aware Navigation

Philip Scales, Véronique Aubergé, Olivier Aycard
1 citations
Social Robot Interaction and HRI
0.64
article

Inducing Social Perceptions of a Mobile Robot for Human-Aware Navigation

Philip Scales, Véronique Aubergé, Olivier Aycard
article en
1 citations

Abstract

Human-aware navigation and Social Navigation are growing fields of robotics, attempting to tackle challenging navigation problems in human environments. One difficult aspect is understanding how a mobile robot's navigation behavior impacts the way they are perceived by humans, and how they interact together. In our previous work, we proposed an adaptable navigation architecture. In this paper, we describe how we determine which motion variables should be controlled by our architecture. We take a bottom-up approach by determining which primitive notions of locomotion and appearance have the most impact on people's perceptions of a mobile robot. We present the results of two online and one in-person experiment showing that the manner in which a mobile robot navigates has a significant impact on people's attribution of attitudes and physical properties to the robot.

Institut polytechnique de Grenoble (FR), Centre National de la Recherche Scientifique (FR), Laboratoire d'Informatique de Grenoble (FR), GIPSA-Lab (FR), Université Grenoble Alpes (FR)
Reduced inequalities
Openalex Percentile: Top 24%
Social Robot Interaction and HRI
0.64
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