The Proxemic Influence on Trust in Triadic Human-Robot Interaction: Insights for Tele-Operative Sonography Assessment in Human-in-the-Loop Systems
As robots become more prevalent in society and applied in various workplace sectors, individuals must have an appropriate amount of trust that aligns with robots' or automated systems' actual capabilities, facilitating optimal and safe human-robot interaction. Appropriately calibrated trust levels can enhance robots' safe and successful adoption into our society and their unique applied environments. The current research aims to assess individuals' self-reported trust levels in a triadic human-robot-human interaction concerning a collaborative haptically enabled “sonography” style robot (having tele-operative capabilities) to assess moderators of trust unique to this specific domain. The objectives of the current research are to identify participants' trust levels in a triadic interaction focusing on the operator's proxemic location while operating the robot (1) and to compare self-reported trust levels across conditions suggested by the literature to have an influence (2). A repeated measures ANDVA revealed a significant association between the replicated traditional sonography assessment and participants possessing higher trust levels than all robot-related conditions. Further, participants had greater trust for the smooth and slow-functioning robot than the non-smooth functioning robot. Lastly, the current study's findings suggest that, compared to the other robot-related conditions, the experimenter's location operating the tele-operative robot does not significantly influence participants' trust levels. Future research should consider exploring humans' qualitative perceptions of their interactions with sonography robots and whether trust can be more accurately calibrated over time. Doing so may assist in developing an in-depth understanding of the discrepancies between human-human interaction and human-robot interactions unique to this setting.
Authors
- David Skvarc (ORCID: https://orcid.org/0000-0002-3334-4980)
- Darius Nahavandi (ORCID: https://orcid.org/0000-0002-5007-9584)
- Shady Mohamed (ORCID: https://orcid.org/0000-0002-8851-1635)
- Nicole Gwenith Toomey (ORCID: https://orcid.org/0009-0007-1343-9118)
- Ghazal Rahimzadeh (ORCID: https://orcid.org/0000-0002-5927-3818)
- Parham M. Kebria (ORCID: https://orcid.org/0000-0001-7049-928X)
Institutions
- Deakin University (AU)
- Intelligent Systems Research (United States) (US)
Publication Details
- Published
- 2024-10-06
- DOI
- https://doi.org/10.1109/smc54092.2024.10831164
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Deakin University