Designing an AR facial expression system for human-robots collaboration

Tong, Yanzhang, Zhang, Qiyuan, Munguia Galeano, Francisco ORCID: https://orcid.org/0000-0001-8397-3083 and Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902 2023. Designing an AR facial expression system for human-robots collaboration. Presented at: 28th International Conference on Automation and Computing (ICAC), Birmingham, UK, 30 August - 1 September 2023. Proceedings of 28th International Conference on Automation and Computing. IEEE, 10.1109/ICAC57885.2023.10275175

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Abstract

In recent years, Human-Robot Collaboration (HRC) has become a significant research field in industry 4.0. However, most research in robotics focuses more on technical aspects and less on the user experience (UX) including important psychological states, such as trust. Evidence suggests that robots that display facial expressions improve the trust and safety of the operator. In this paper, we introduce an augmented reality (AR) approach that uses facial expressions to convey safety-critical messages in HRC tasks, aiming to increase the operator's trust. In our experiment, we used an HRC scenario that comprises a collaborative task in which a user assembled a block-building pattern with the help of a robot. For one condition, we designed an AR display with an animated face, through which expressions varied according to the state of the HRC task. For the other condition, the face was displayed on a screen. We then measured the user's trust with self-report instruments. Despite that facial expressions were shown to convey robot state information accurately, no clear evidence was found that AR could improve trust in HRC. Possible causes of the results are discussed, including unfamiliarity with the AR technology.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	IEEE
ISBN:	9798350335866
Date of First Compliant Deposit:	27 June 2023
Date of Acceptance:	22 June 2023
Last Modified:	21 Nov 2023 10:19
URI:	https://orca.cardiff.ac.uk/id/eprint/160634

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