Sound Matters: Auditory Detectability of Mobile Robots

Fuente: arXiv
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Autores principales: Agrawal, Subham, Wessels, Marlene, de Heuvel, Jorge, Kraus, Johannes, Bennewitz, Maren
Formato: Preprint
Publicado: 2024
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author Agrawal, Subham
Wessels, Marlene
de Heuvel, Jorge
Kraus, Johannes
Bennewitz, Maren
author_facet Agrawal, Subham
Wessels, Marlene
de Heuvel, Jorge
Kraus, Johannes
Bennewitz, Maren
contents Mobile robots are increasingly being used in noisy environments for social purposes, e.g. to provide support in healthcare or public spaces. Since these robots also operate beyond human sight, the question arises as to how different robot types, ambient noise or cognitive engagement impacts the detection of the robots by their sound. To address this research gap, we conducted a user study measuring auditory detection distances for a wheeled (Turtlebot 2i) and quadruped robot (Unitree Go 1), which emit different consequential sounds when moving. Additionally, we also manipulated background noise levels and participants' engagement in a secondary task during the study. Our results showed that the quadruped robot sound was detected significantly better (i.e., at a larger distance) than the wheeled one, which demonstrates that the movement mechanism has a meaningful impact on the auditory detectability. The detectability for both robots diminished significantly as background noise increased. But even in high background noise, participants detected the quadruped robot at a significantly larger distance. The engagement in a secondary task had hardly any impact. In essence, these findings highlight the critical role of distinguishing auditory characteristics of different robots to improve the smooth human-centered navigation of mobile robots in noisy environments.
format Preprint
id arxiv_https___arxiv_org_abs_2404_06807
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Sound Matters: Auditory Detectability of Mobile Robots
Agrawal, Subham
Wessels, Marlene
de Heuvel, Jorge
Kraus, Johannes
Bennewitz, Maren
Robotics
Mobile robots are increasingly being used in noisy environments for social purposes, e.g. to provide support in healthcare or public spaces. Since these robots also operate beyond human sight, the question arises as to how different robot types, ambient noise or cognitive engagement impacts the detection of the robots by their sound. To address this research gap, we conducted a user study measuring auditory detection distances for a wheeled (Turtlebot 2i) and quadruped robot (Unitree Go 1), which emit different consequential sounds when moving. Additionally, we also manipulated background noise levels and participants' engagement in a secondary task during the study. Our results showed that the quadruped robot sound was detected significantly better (i.e., at a larger distance) than the wheeled one, which demonstrates that the movement mechanism has a meaningful impact on the auditory detectability. The detectability for both robots diminished significantly as background noise increased. But even in high background noise, participants detected the quadruped robot at a significantly larger distance. The engagement in a secondary task had hardly any impact. In essence, these findings highlight the critical role of distinguishing auditory characteristics of different robots to improve the smooth human-centered navigation of mobile robots in noisy environments.
title Sound Matters: Auditory Detectability of Mobile Robots
topic Robotics
url https://arxiv.org/abs/2404.06807