Walk Along: An Experiment on Controlling the Mobile Robot “Spot” with Voice and Gestures

Robots are becoming more capable and can autonomously perform tasks such as navigating between locations. However, human oversight remains crucial. This study compared two touchless methods for directing mobile robots: voice control and gesture control, to investigate the efficiency of these methods and the preference of users. We tested these methods in two conditions: one in which participants remained stationary and one in which they walked freely alongside the robot. We hypothesized that walking alongside the robot would result in higher intuitiveness ratings and improved task performance, based on the idea that walking promotes spatial alignment and reduces the effort required for mental rotation. In a 2 × 2 within-subject design, 218 participants guided the quadruped robot Spot along a circuitous route with multiple 90 \(^{\circ}\) turns using rotate left, rotate right, and walk forward commands. After each trial, participants rated the intuitiveness of the command mapping, while post-experiment interviews were used to gather the participants’ preferences. Results showed that voice control combined with walking with Spot was the most favored and intuitive, whereas gesture control while standing caused confusion for left/right commands. Nevertheless, 29% of participants preferred gesture control, citing increased task engagement and visual congruence as reasons. An odometry-based analysis revealed that participants often followed behind Spot, particularly in the gesture control condition, when they were allowed to walk. In conclusion, voice control with walking produced the best outcomes. Improving physical ergonomics and adjusting gesture types could make gesture control more effective.

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Publication Details

Journal
ACM Transactions on Human-Robot Interaction
Published
2025-04-12
DOI
https://doi.org/10.1145/3729540
Citations
1
Primary Topic
Social Robot Interaction and HRI
Type
article
Field-Weighted Citation Impact
2.44
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article

Walk Along: An Experiment on Controlling the Mobile Robot “Spot” with Voice and Gestures

Dimitra Dodou, Joost de Winter, Yke Bauke Eisma, Harleigh Seyffert et al.
1 citations
ACM Transactions on Human-Robot Interaction
Social Robot Interaction and HRI
2.44
article

Walk Along: An Experiment on Controlling the Mobile Robot “Spot” with Voice and Gestures

Dimitra Dodou, Joost de Winter, Yke Bauke Eisma, Harleigh Seyffert, Renchi Zhang, Jesse van der Linden
article en
1 citations

Abstract

Robots are becoming more capable and can autonomously perform tasks such as navigating between locations. However, human oversight remains crucial. This study compared two touchless methods for directing mobile robots: voice control and gesture control, to investigate the efficiency of these methods and the preference of users. We tested these methods in two conditions: one in which participants remained stationary and one in which they walked freely alongside the robot. We hypothesized that walking alongside the robot would result in higher intuitiveness ratings and improved task performance, based on the idea that walking promotes spatial alignment and reduces the effort required for mental rotation. In a 2 × 2 within-subject design, 218 participants guided the quadruped robot Spot along a circuitous route with multiple 90 \(^{\circ}\) turns using rotate left, rotate right, and walk forward commands. After each trial, participants rated the intuitiveness of the command mapping, while post-experiment interviews were used to gather the participants’ preferences. Results showed that voice control combined with walking with Spot was the most favored and intuitive, whereas gesture control while standing caused confusion for left/right commands. Nevertheless, 29% of participants preferred gesture control, citing increased task engagement and visual congruence as reasons. An odometry-based analysis revealed that participants often followed behind Spot, particularly in the gesture control condition, when they were allowed to walk. In conclusion, voice control with walking produced the best outcomes. Improving physical ergonomics and adjusting gesture types could make gesture control more effective.

ACM Transactions on Human-Robot InteractionVol. 14(4)
Delft University of Technology (NL)
Openalex Percentile: Top 14%
Social Robot Interaction and HRI
2.44
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