Sensing Robots and Social Odor: How Relational Engagement and Trust Change

Exploring the interaction dynamics between humans and robots also entails examining the exchange of multisensory signals. In this light, this study explores the role of social odors (putative pheromones) in shaping human-robot interactions (HRI) beyond the conventional focus on visual and auditory cues. Our research examines how these odors influence relational engagement (RE; assessed as co-presence and social presence) and trust (dispositional and situational) during interactions with the humanoid social robot (HSR) NAO. The robot was also equipped with a male or female voice, to better counteract odor-related gender differences. Thirty participants engaged in storytelling sessions with NAO under different sensory conditions. Our findings indicate odors significantly affecting trust, especially when resembling female pheromones. Conversely, odors had a nuanced influence on RE, despite participants reporting greater CoPre than SoPre. Additionally, a bidirectional relationship between SoPre and trust emerged, reinforced by sensory congruence. These results highlight the significance of sensory alignment in shaping socio-relational and trust dynamics and emphasize the potential of olfactory stimuli in enhancing human-robot interactions. By deepening our understanding of the complex interplay among olfactory cues, voice gender, RE, and trust within HRIs, we provide valuable insights for crafting and deploying HSRs that are more relatable and trustworthy.

Publication Details

Journal
Research Explorer (The University of Manchester)
Published
2025-03-24
Primary Topic
Social Robot Interaction and HRI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sensing Robots and Social Odor: How Relational Engagement and Trust Change

Research Explorer (The University of Manchester)
Social Robot Interaction and HRI
article

Sensing Robots and Social Odor: How Relational Engagement and Trust Change

article en

Abstract

Exploring the interaction dynamics between humans and robots also entails examining the exchange of multisensory signals. In this light, this study explores the role of social odors (putative pheromones) in shaping human-robot interactions (HRI) beyond the conventional focus on visual and auditory cues. Our research examines how these odors influence relational engagement (RE; assessed as co-presence and social presence) and trust (dispositional and situational) during interactions with the humanoid social robot (HSR) NAO. The robot was also equipped with a male or female voice, to better counteract odor-related gender differences. Thirty participants engaged in storytelling sessions with NAO under different sensory conditions. Our findings indicate odors significantly affecting trust, especially when resembling female pheromones. Conversely, odors had a nuanced influence on RE, despite participants reporting greater CoPre than SoPre. Additionally, a bidirectional relationship between SoPre and trust emerged, reinforced by sensory congruence. These results highlight the significance of sensory alignment in shaping socio-relational and trust dynamics and emphasize the potential of olfactory stimuli in enhancing human-robot interactions. By deepening our understanding of the complex interplay among olfactory cues, voice gender, RE, and trust within HRIs, we provide valuable insights for crafting and deploying HSRs that are more relatable and trustworthy.

Research Explorer (The University of Manchester)
Gender equality
Openalex Percentile: Top 33%
Social Robot Interaction and HRI
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.