音は重要:移動ロボットの聴覚的な検出可能性
Sound Matters: Auditory Detectability of Mobile Robots
車輪型と四足歩行型ロボットの移動音が、周囲の騒音や二次課題の有無によってどの程度検出されやすいかをユーザー実験で比較した。
著者: Subham Agrawal, Marlene Wessels, Jorge de Heuvel, Johannes Kraus, Maren Bennewitz
分類: cs.RO
原文アブストラクト
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.
