Franziska Legler

Emerging technologies offer cultural institutions opportunities to expand their audiences and make their content more accessible. Augmented Virtuality (AV), which integrates real-world content into virtual environments, shows particular potential. It enables the transmission of live or pre-recorded stage performances, such as concerts and theater productions, from the stage to virtual audiences via increasingly affordable head-mounted displays (HMDs). However, as AV remains under-researched, little is known about which recording features enable an immersive user experience while maintaining cost-efficiency—an essential requirement for resource-constrained cultural institutions. In this context, we investigate the influence of features of audio and video recordings on key dimensions of user experience in the use case of a real opera performance integrated into a virtual opera house. We conducted a 2 × 2 within-subjects study with 30 participants to measure the effects of 2D versus 3D videos and stereophonic versus spatial audio rendering on several key dimensions of user experience. The results show that spatial audio has a positive impact on Place Illusion, whereas video dimensionality had no significant effect. Recommendations for the design of AV applications are derived from study results, aiming at balancing immersive user experience and cost-efficiency for virtual cultural participation.

Introduction: Recent technological advances in human-robot collaboration (HRC) allow for increased efficiency and flexibility of production in Industry 5.0 while providing a safe workspace. Despite objective safety, research has shown subjective trust in robots to shape the interaction of humans and robots. While antecedents of trust have been broadly examined, empirical studies in HRC investigating the relationship between trust and industry-relevant outcomes are scarce and the importance of trust regarding its precise effects remains unclear. To advance human-centered automation, this paper investigates the affective, cognitive, and behavioral consequences of trust in robots, and explores whether trust mediates the relationship between industry-relevant characteristics and human-centered HRC outcomes. Methods: In a pseudo real-world test environment, 48 participants performed a manufacturing task in collaboration with a heavy-load robot. Trust, affective experience over time, intention to use, and safety-critical behavior were examined. A 2 × 2 × 2 mixed design varied the availability of feedback, time pressure, and system failures, each expected to affect the level of trust. Results: In the control group, trust remained consistently high across all conditions. System failures and feedback significantly reduced trust, whereas time pressure had no effect. System failures further increased negative affective experience, while feedback reduced safety-critical behavior. Trust was unrelated to affective experience but positively related to safety-critical behavior and intention to use. The relationship between feedback and safety-critical behavior, as well as intention to use, was significantly mediated by trust. Discussion: Highly relevant for implementation, the control group showed a tendency toward overtrust during collaboration, evidenced by disregarding system failures. The results indicate that implementing a feedback system alongside the simulation of safe system failures has the potential to adjust trust toward a more appropriate level, thereby reducing safety-critical behavior. Based on these findings, the paper posits several implications for the design of HRC and gives directions for further research.

Today’s research on fenceless human–robot collaboration (HRC) is challenged by a relatively slow development of safety features. Simultaneously, design recommendations for HRC are requested by the industry. To simulate HRC scenarios in advance, virtual reality (VR) technology can be utilized and ensure safety. VR also allows researchers to study the effects of safety-restricted features like close distance during movements and events of robotic malfunctions. In this paper, we present a VR experiment with 40 participants collaborating with a heavy-load robot and compare the results to a similar real-world experiment to study transferability and validity. The participant’s proximity to the robot, interaction level, and occurring system failures were varied. State anxiety, trust, and intention to use were used as dependent variables, and valence and arousal values were assessed over time. Overall, state anxiety was low and trust and intention to use were high. Only simulated failures significantly increased state anxiety, reduced trust, and resulted in reduced valence and increased arousal. In comparison with the real-world experiment, non-significant differences in all dependent variables and similar progression of valence and arousal were found during scenarios without system failures. Therefore, the suitability of applying VR in HRC research to study safety-restricted features can be supported; however, further research should examine transferability for high-intensity emotional experiences.

Handing over objects is a collaborative task that requires participants to synchronize their actions in terms of space and time, as well as their adherence to social standards. If one participant is a social robot and the other a visually impaired human, actions should favorably be coordinated by voice. User requirements for such a Voice-User Interface (VUI), as well as its required structure and content, are unknown so far. In our study, we applied the user-centered design process to develop a VUI for visually impaired humans and humans with full sight. Iterative development was conducted with interviews, workshops, and user tests to derive VUI requirements, dialog structure, and content. A final VUI prototype was evaluated in a standardized experiment with 60 subjects who were visually impaired or fully sighted. Results show that the VUI enabled all subjects to successfully receive objects with an error rate of only 1.8%. Likeability and accuracy were evaluated best, while habitability and speed of interaction were shown to need improvement. Qualitative feedback supported and detailed results, e.g., how to shorten some dialogs. To conclude, we recommend that inclusive VUI design for social robots should give precise information for handover processes and pay attention to social manners.