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.

翻译：移动机器人正日益被应用于嘈杂环境中以实现社交目的，例如在医疗保健或公共场所提供支持。由于这些机器人也在人类视线之外运行，这就引出了一个问题：不同类型的机器人、环境噪声或认知参与如何影响人们通过声音对机器人的探测。为填补这一研究空白，我们开展了一项用户研究，测量了轮式机器人（Turtlebot 2i）和四足机器人（Unitree Go 1）的听觉探测距离，这两种机器人在移动时会发出不同的伴随声音。此外，我们在研究中还控制了背景噪声水平，并让参与者同时执行一项次要任务。结果显示，四足机器人的声音探测效果显著优于轮式机器人（即在更远距离被探测到），这表明运动机制对听觉可探测性具有重要影响。随着背景噪声增大，两种机器人的可探测性均显著下降。但即使在强背景噪声下，参与者仍能在显著更远的距离探测到四足机器人。次要任务的参与则几乎未产生影响。本质上，这些发现凸显了区分不同机器人听觉特征的至关重要性，以提升移动机器人在嘈杂环境中实现以人为中心的流畅导航。