Exploring how robots impact human cognition and emotions has become increasingly important as robots gradually become ubiquitous in our lives. In this study, we investigate the impact of robotic presence on human cognition and emotion by examining various robot parameters such as anthropomorphism, number of robots, and multi-robot motion patterns. 16 participants completed two cognitive tasks in the presence of anthropomorphic and non-anthropomorphic robots, alone, and with a human nearby. The non-anthropomorphic robot conditions were further varied in the number of robots and their motion patterns. We find that increasing the number of non-anthropomorphic robots generally leads to slower performance, but coordinated patterned motions can lower the completion time compared to random movements. An anthropomorphic robot induces an increased level of feelings of being judged compared to a non-anthropomorphic robot. These findings provide preliminary insights into how designers or users can purposefully integrate robots into our environment by understanding the effects of anthropomorphism, number of robots, and multi-robot motion patterns on human cognition and emotion.

We introduce the concept of programmable actuated fidgeting, a type of fidgeting that involves devices integrated with actuators, sensors, and computing to enable a customizable interactive fidgeting experience. In particular, we explore the potential of a swarm of tabletop robots as an instance of programmable actuated fidgeting as robots are becoming increasingly available. Through ideation sessions among researchers and feedback from the participants, we formulate the design space for SwarmFidget, where swarm robots are used to facilitate programmable actuated fidgeting. To gather user impressions, we conducted an exploratory study where we introduced the concept of SwarmFidget to twelve participants and had them experience and provide feedback on six example fidgeting interactions. Our study demonstrates the potential of SwarmFidget for facilitating fidgeting interaction and provides insights and guidelines for designing effective and engaging fidgeting interactions with swarm robots. We believe our work can inspire future research in the area of programmable actuated fidgeting and open up new opportunities for designing novel swarm robot-based fidgeting systems.

The continuous growth in availability and access to data presents a major challenge to the human analyst. As the manual analysis of large and complex datasets is nowadays practically impossible, the need for assisting tools that can automate the analysis process while keeping the human analyst in the loop is imperative. A large and growing body of literature recognizes the crucial role of automation in Visual Analytics and suggests that automation is among the most important constituents for effective Visual Analytics systems. Today, however, there is no appropriate taxonomy nor terminology for assessing the extent of automation in a Visual Analytics system. In this article, we aim to address this gap by introducing a model of levels of automation tailored for the Visual Analytics domain. The consistent terminology of the proposed taxonomy could provide a ground for users/readers/reviewers to describe and compare automation in Visual Analytics systems. Our taxonomy is grounded on a combination of several existing and well-established taxonomies of levels of automation in the human-machine interaction domain and relevant models within the visual analytics field. To exemplify the proposed taxonomy, we selected a set of existing systems from the event-sequence analytics domain and mapped the automation of their visual analytics process stages against the automation levels in our taxonomy.

In this paper, we study how a co-located robot affects human motivation and emotion. In particular, we examine the role of the co-located robot’s anthropomorphism, as well as the effects of the human’s personality and gender. To study this, we conducted an online experiment, where 182 participants completed a repetitive task, either easy or hard, in one of the four conditions: in the presence of a non-anthropomorphic robot, an anthropomorphic robot, another human, or alone. For each condition, we analyzed the number of repetitions and the total time users spent, which we treated as the proxy of their motivation, as well as their self-reported emotional states. The study results suggest that the presence of a non-anthropomorphic robot has the potential to lead to a higher level of motivation and a more desirable affective state for users than the presence of an anthropomorphic robot or another human, especially for introverts and female users during difficult tasks.

A swarm of robots can accomplish more than the sum of its parts, and swarm systems will soon see increased use in applications ranging from tangible interfaces to search and rescue teams. However, effective human control of robot swarms has been shown to be demonstrably more difficult than controlling a single robot, and swarm-specific interactions methodologies are relatively underexplored. As we envision even non-expert users will have more daily in-person encounters with different numbers of robots in the future, we present a user-defined set of control interactions for tabletop swarm robots derived from an elicitation study. We investigated the effects of number of robots and proximity on the user's interaction and found significant effects. For instance, participants varied between using 1-2 fingers, one hand, and both hands depending on the group size. We also provide general design guidelines such as preferred interaction modality, common strategies, and a high-agreement interaction set.

In the age of extensive industrial digitalization, industrial operators are facing increasing pressure from the growing amount of data being delivered to industrial control rooms. Humans' limited perceptual system is the bottleneck when it comes to processing large volumes of information. Too many screens crammed with textual and numerical data make the user disoriented in information potentially leading to fatal mistakes and insufficient situation awareness. This paper explores possibilities of guiding operators' attention to the most urgent information by means of visual aid systems. In this work, two concepts of such systems were developed and evaluated in a lab environment. The evaluation results indicate a clear benefit of using the developed concepts.

Novel autonomous search and rescue systems, although powerful, still require a human decision-maker involvement. In this project, we focus on the human aspect of one such novel autonomous SAR system. Relying on the knowledge gained in a field study, as well as through the literature, we introduced several extensions to the system that allowed us to achieve a more user-centered interface. In the evaluation session with a rescue service specialist, we received positive feedback and defined potential directions for future work.

The health and medical institutes and hospitals are facing several challenges in the short and long term, i.e. demographic changes, demands on improving quality, limited resources and cost requirements. To cope with these challenges, the health care sector needs to become more efficient, while maintaining and improving the quality of care. Efficient and transparent information flow across the whole system plays a key role even in this context. Being able to analyze the patient flows as the first step will provide the possibility to more efficiently manage medical resources and better serve incoming patients. In this work, we have developed a web-based portal for interactive analysis of patient flow data to assist hospital authorities to improve and optimize the time and quality of the provided services. The developed tool facilitates short and long term optimization of resource allocation by analyzing the past, as well as current, patient flows, identifying bottlenecks and exploring the reasons for the occurred waiting times.

This paper describes an explorative design study conducted in the scope of a collaborative research project in the district heating domain. In the scope of the project, we have arranged extensive field studies at two power plants to understand the workflows, problems, and needs of industrial operators. We relied on the gained knowledge to design and develop novel visual interfaces that would communicate the overall status of the district heating system at-a-glance. We aimed at exploring potential directions and alternatives beyond conventional industrial interfaces. One particular aspect of our research was related to how the physicality of the underlying industrial processes can be expressed by purely visual means. The paper introduces three high-fidelity prototypes demonstrating the novel visualizations developed. The paper explains the design choices made, namely the relation between the selected visual encodings to the requirements of the industrial operators' tasks. Preliminary evaluation indicates industrial operators' interest in the designed solutions. Future work will incorporate an extensive qualitative evaluation on site.

In recent years, advances in sensors, Internet and communication technologies opened many promising opportunities for remote services of industrial robots. With remote service applications, potential problems in robot systems can be detected before they happen, and prevented pro-actively avoiding costly production shut-downs. However, to be able to effectively perform remote service operations, remote support engineers need to analyse vast amounts of information. For a remote support engineer to be able to manage such amount of data, effective data visualization is crucial. Based on field studies and collected needs of support engineers working with industrial robots, we have designed and developed a prototype, i.e. one possible solution of an effective industrial fleet visualization, applied on the overheated robots use case. The initial validation of the prototype showed the benefits of such visual data presentation, as well as future directions.

Tools used for remote collaboration and assistance within the industrial sector have remained unchanged for a long time. We introduce a concept called "Expert on Wheels" as the next step in development of remote collaboration tools. "Expert on Wheels" is a mobile tele-presence robot designed to support collaboration between a field worker and a remote expert. This paper presents an exploratory research study, in which "Expert on Wheels" was evaluated with target users as well as in a lab environment. The results indicate that the system has potential but requires improvements in key areas such as the situation awareness of the expert and the system's mobility as a whole. We conclude by discussing if and how such systems could be accepted and useful in different industrial settings.

Augmented Reality (AR) enhances real-world view with additional virtual information. This technique can be applied to a variety of industrial applications. It can be used to localize equipment in an industrial plant, to identify a dedicated device or to show its configuration. In addition, AR can be used in remote service situations, where remote experts are guiding local field workers in maintenance tasks. In this paper, we will describe the opportunities of utilizing the AR technology in industrial settings. Besides the presentation of the envisioned use cases, we will present some prototypes that were developed and evaluated during our work.