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Robots Have Been Seen and Not Heard: Effects of Consequential Sounds on Human-Perception of Robots

Aimee Allen, Tom Drummond, Dana Kulić

TL;DR

This study investigates how consequential sounds produced by robots influence human perception in shared environments. Using a between-subjects video study with five diverse robots and 182 participants, it finds that consequential sounds significantly worsen associated affect, distraction, and willingness to colocate, while likeability remains largely unaffected. Regression analyses show robust main effects of sound with minimal robot-by-sound interactions, underscoring a general negative impact of robot sounds on perception. The findings highlight the importance of sound design in HRI and motivate development of strategies to attenuate or transform robot sounds to facilitate acceptance and safe cohabitation in workplaces, homes, and public spaces.

Abstract

Robots make compulsory machine sounds, known as `consequential sounds', as they move and operate. As robots become more prevalent in workplaces, homes and public spaces, understanding how sounds produced by robots affect human-perceptions of these robots is becoming increasingly important to creating positive human robot interactions (HRI). This paper presents the results from 182 participants (858 trials) investigating how human-perception of robots is changed by consequential sounds. In a between-participants study, participants in the sound condition were shown 5 videos of different robots and asked their opinions on the robots and the sounds they made. This was compared to participants in the control condition who viewed silent videos. Consequential sounds correlated with significantly more negative perceptions of robots, including increased negative `associated affects', feeling more distracted, and being less willing to colocate in a shared environment with robots.

Robots Have Been Seen and Not Heard: Effects of Consequential Sounds on Human-Perception of Robots

TL;DR

This study investigates how consequential sounds produced by robots influence human perception in shared environments. Using a between-subjects video study with five diverse robots and 182 participants, it finds that consequential sounds significantly worsen associated affect, distraction, and willingness to colocate, while likeability remains largely unaffected. Regression analyses show robust main effects of sound with minimal robot-by-sound interactions, underscoring a general negative impact of robot sounds on perception. The findings highlight the importance of sound design in HRI and motivate development of strategies to attenuate or transform robot sounds to facilitate acceptance and safe cohabitation in workplaces, homes, and public spaces.

Abstract

Robots make compulsory machine sounds, known as `consequential sounds', as they move and operate. As robots become more prevalent in workplaces, homes and public spaces, understanding how sounds produced by robots affect human-perceptions of these robots is becoming increasingly important to creating positive human robot interactions (HRI). This paper presents the results from 182 participants (858 trials) investigating how human-perception of robots is changed by consequential sounds. In a between-participants study, participants in the sound condition were shown 5 videos of different robots and asked their opinions on the robots and the sounds they made. This was compared to participants in the control condition who viewed silent videos. Consequential sounds correlated with significantly more negative perceptions of robots, including increased negative `associated affects', feeling more distracted, and being less willing to colocate in a shared environment with robots.
Paper Structure (18 sections, 1 equation, 3 figures, 1 table)

This paper contains 18 sections, 1 equation, 3 figures, 1 table.

Figures (3)

  • Figure 1: Robots featured in this study (top left to bottom right): Quadrotor; Go1 (Unitree); Pepper (SoftBank Robotics); Jackal (ClearPath Robotics); Yanshee (UBTECH).
  • Figure 2: Data distributions between conditions for all 4 scales, (1) = negative to (7) = positive perception. Means (coloured dots) and 95% confidence intervals (vertical lines) are shown between conditions.
  • Figure 3: Data distributions across robots and conditions for all 4 scales, (1) = negative to (7) = positive perception. Means (coloured dots) and 95% confidence intervals (vertical lines) are shown between condition pairs.