Recent research has demonstrated the potential for representing intelligent guidance using multi-modal cues, yet few guidelines or processes exist to guide the design of such a system. In this article, we seek to address this gap by investigating the design of multi-modal assistant systems for setting the optimal parameters in industrial plants. We present the results of two user studies conducted with a total of 37 participants to evaluate the effectiveness and experience of different combinations of visual ( Highlights and Ambient lights) and haptic ( Clicks and Vibration ) modalities for providing intelligent dynamic guidance. Our findings demonstrate that providing the intelligent guidance with the multi-modality of Highlights+Ambient resulted in shorter task duration and higher practicality than Ambient lights alone. Regarding task accuracy, the Highlights and Vibration outside-zone guidance resulted in no failed attempts. Moreover, Highlights+Ambient+Vibration guidance was rated as having lower usability than Highlights+Ambient , and higher mental demand than merely Highlights .

The integration of humans and robots in real-world scenarios requires the development of cooperative environments where seamless collaboration is supported by intuitive user interfaces and calibrated trust. This paper reports on a virtual reality user study (N = 22) conducted in the context of collaborative interaction with a semi-autonomous robotic forklift. In the study, we investigated the relationship between perceived user experience of a human-robot interface and trust, as well as factors influencing users’ choices between two error-handling methods (manual vs. automatic recalibration) to solve a system failure. No differences in terms of trust attribution emerged between error-handling options. However, choosing the manual control yielded higher pragmatic quality of user experience and satisfaction of competence need ratings. Positive correlations between trust, user experience, and needs satisfaction were also found. Our results offer insights into user experience and trust-building in industrial human-robot interaction, shedding light on the critical role of human factors in designing effective automation systems.

Recent research has demonstrated the potential for representing intelligent guidance using multi-modal cues, yet few guidelines or processes exist to guide the design of such a system. In this paper, we seek to address this gap by investigating the design of multi-modality assistant systems for setting the optimal parameters in industrial plants. We present the results of our study conducted with 22 participants to evaluate the effectiveness and experience of different combinations of visual (Highlights and Ambient lights) and haptic (Clicks and Vibration) modalities for providing intelligent dynamic guidance. Our findings demonstrate that providing the intelligent guidance with the multi modality of Highlights+Ambient resulted in shorter task duration and higher practicality than Ambient lights alone. Moreover, Highlights+Ambient+Vibration guidance was rated with lower usability than Highlights+Ambient as well as higher mental demand than merely Highlights.

Access to art and cultural heritage is an important aspect of the well-being of humans. Within the BeauCoup project, we aim to create solutions to improve access to cultural heritage for older adults with and without impairments. In this paper, we present tangible, interactive postcards, which were developed in a user-centered design process within the project. These digital tangible postcards are a cheap, ubiquitous and easily transportable solution to make artworks - especially paintings - interactively accessible to people with visual impairments. We describe the developed solutions and will strive to discuss with the community the general concept, improvements and further application areas.

Investigating application areas for utilizing robots to support human workers is a continuing concern within human robot collaboration. In this paper, we focus on surface repair and finishing processes in which robots support skilled workers in task execution. We conducted a user study which investigates novel, pen-based human robot interaction modalities for collaborative spot repair processes in a Virtual Reality (VR) setting. Our findings show that participants preferred a test condition in which all interaction with the robot took place directly on the work piece. Furthermore, the interaction modality had an impact on objective performance indicators. These findings are discussed in the context of designing intuitive interfaces for collaborative robots in industrial settings.