Högskolan i Skövde

Categorization of rhythmic patterns is prevalent in musical practice, an example of this being the transcription of (possibly not strictly metrical) music into musical notation. In this article we implement a dynamical systems' model of rhythm categorization based on the resonance theory of rhythm perception developed by Large (2010). This model is used to simulate the categorical choices of participants in two experiments of Desain and Honing (2003). The model accurately replicates the experimental data. Our results support resonance theory as a viable model of rhythm perception and show that by viewing rhythm perception as a dynamical system it is possible to model central properties of rhythm categorization.

Categorical perception is a well studied phenomenon in, for example, colour perception, phonetics and music. In this article we implement a dynamical systems model of categorical rhythm perception based on the resonance theory of rhythm perception developed by Large (2010). This model is used to simulate the categorical choices of participants in two experiments of Desain and Honing (2003). The model is able to accurately replicate the experimental data. Our results supports that resonance theory is a viable model of rhythm perception and they show that by viewing rhythm perception as a dynamical system it is possible to model properties of categorical perception.

We demonstrate how nanofluidic channels can be used as a tool to rapidly determine the number and sizes of plasmids in bacterial isolates. Each step can be automated at low cost, opening up opportunities for general use in microbiology labs.

The field Human-Robot Interaction (HRI) involves new forms of social interactions that are dependent on the many and different earlier expectations of humans. In this study, the impact of linguistic framing on students' expectations and user experiences when being introduced to social robots in an educational setting were investigated. An empirical case study involved the social robot Pepper and 10 students aged 16–19. The introduction to Pepper utilized two forms of linguistic framing: positive and negative terms. Pre- and post-interaction interviews were conducted to assess the students' expectations and experiences. Assessments to measure negative attitudes toward robots and user experiences were conducted using the NARS and Godspeed questionnaires. Furthermore, filmed observations of the students' interactions with Pepper were used to provide additional insights. Results of the study showed that students' expectations and experiences varied depending on the type of introduction and linguistic framing utilized. While none of the differences among the questionnaire responses were statistically significant, the trends were in line with the clear results from the interviews and observations.

Industry 4.0 aims to support the factory of the future, which involves increased amounts of information systems and new ways of using automation. One new usage is collaboration between human and industrial robot in manufacturing, with both partners sharing work on a single task. Supporting human-robot collaboration (HRC) requires understanding the requirements of HRC as well as the differences to existing approaches where the goal is more automation, such as in the case of self-driving cars. We propose a framework that we call levels of collaboration to support this, and posit that this framework supports a mental model conducive to the design of lines incorporating HRC.

Industry 4.0 aims to support the factory of the future, involving increased use of information systems and new ways of using automation, such as collaboration where a robot and a human share work on a single task. We propose a classification of collaboration levels for Human-Robot collaboration (HRC) in manufacturing that we call levels of collaboration (LoC), formed to provide a conceptual model conducive to the design of assembly lines incorporating HRC. This paper aims to provide a more theoretical foundation for such a tool based on relevant theories from cognitive science and other perspectives of human-technology interaction, strengthening the validity and scientific rigour of the envisioned LoC tool. The main contributions consist of a theoretical grounding to motivate the transition from automation to collaboration, which are intended to facilitate expanding the LoC classification to support HRC, as well as an initial visualization of the LoC approach. Future work includes fully defining the LoC classification as well as operationalizing functionally different cooperation types. We conclude that collaboration is a means to an end, so collaboration is not entered for its own sake, and that collaboration differs fundamentally from more commonly used views where automation is the focus.

Perception is a vast subject to study. One way to approach and study it might therefore be to break down the concept into smaller pieces. Specific modes of sensation, mechanisms, phenomena, or contexts might be selected as the proxy or starting point for addressing perception as a whole. Another approach would be to widen the concept, and attempt to study perception through the larger context of which it is a part. I have, in this thesis, attempted the latter strategy, by emphasising an existential perspective, and examine the role and nature of perception through that lens.

The larger perspective of broadening the scope does not specifically allow for better answers, but rather different kinds of answers, providing complementary ways of exploring what it means to be an artificial or natural agent, and what consequences that can have for the access to, as well as representation, processing, and communication of information. A broader stance can also facilitate exploration of questions regarding larger perspectives, such as the relation between individual agents, as well as their place in larger structures such as societies and cyber-physical systems.

In this thesis I use existential phenomenology to frame the concept of perception, while drawing from theories in biology and psychology. My work has a particular focus on human-robot interaction, a field of study at a fascinating intersection of humans designing, using, and communicating with something human-made, partially human-like, yet distinctly non-human. The work is also applied to some aspects of the traffic domain which, given the increasing interest in self-driving vehicles, is partially another instance of complex and naturalistic human-robot interaction.

Ultimately, I argue for a pluralistic and pragmatic approach to the understanding of perception, and its related concepts. To understand a system of agents as they interact, it is not only necessary to acknowledge their respective circumstances, but take serious the idea that none of the agents’ constructed worlds are more or less real, they might only be more or less relevant in relation to specific contexts, perspectives, or needs. Such an approach is particularly relevant when addressing the complexities of the increasingly urgent sustainability challenges.

Functional tones is a concept that originates in theoretical biology and resembles how the concept ‘affordances’ is used. Both functional tones and affordances are concepts dealing with particularly salient features in an individual’s immediate environment. The concept of affordances has proven useful for practitioners of usability and design as it supports intuitive ways of classifying how action possibilities match between a person and an object [1]. Functional tones have, however, thus far remained obscure among practitioners, despite functional tones having a stronger theoretical foundation and facilitates a deeper and more human-centred analysis of interaction. The functional tones related to an object depend not only on the modes of sensation and action the perceiver is capable of, but also more subjective aspects such as experience, motivation and emotions. Using functional tones in design or analysis of interaction provides a fundamentally user experience centred perspective while avoiding the philosophical luggage of affordances.

There are numerous examples of role-playing being adapted and included as a pedagogical technique in teaching, including in higher education. For example, teachers might simulate different scenarios, and role-play different stakeholders and users, in order to create more experiential types of learning environments. Role-playing can also provide an opportunity for students to actively explore, reflect upon and personalise the material that is studied. Similar techniques can be seen in User Experience Design (UXD), wherepractitioners create personas and scenarios to describe representative and typical usersand use-cases. In this report, we propose an alternative use to the more traditional way of using personas and scenarios in academiaas well as in industry: as character sheets and role-playing. Instead of being more analytical and descriptive tools in the design process, our role-playing approach invites exploration and personal interaction. Putting such character sheets into action allows the design team to interact with hypothetical, but typical users, thus providing a richer understanding of their context, and facilitating an empathetic understanding of the different stakeholders and their sometimes conflicting interests. This is particularly relevant in an educational context, where students are learning and training to improveas designers.

Rapid technical advancements have led to dramatically improved abilities for artificial agents, and thus opened up for new ways of cooperation between humans and them, from disembodied agents such as Siris to virtual avatars, robot companions, and autonomous vehicles. It is therefore relevant to study not only how to maintain appropriate cooperation, but also where the responsibility for this resides and/or may be affected. While there are previous organisations and categorisations of agents and HAI research into taxonomies, situations with highly responsible artificial agents are rarely covered. Here, we propose a way to categorise agents in terms of such responsibility and agent autonomy, which covers the range of cooperation from humans getting help from agents to humans providing help for the agents. In the resulting diagram presented in this paper, it is possible to relate different kinds of agents with other taxonomies and typical properties. A particular advantage of this taxonomy is that it highlights under what conditions certain effects known to modulate the relationship between agents (such as the protégé effect or the "we"-feeling) arise.

The paper investigates the potential of electric bikes as a sustainable alternative for local transportation during vacations in rural areas, replacing mainly transportation by car. Our starting point is that a key to behaviour change in the context of tourism and leisure travels is to make the sustainable travel option the most desirable option for the traveller. We study this by exploring three different electric bike offers in the area of Skaraborg, Sweden, and analysing the experience of the cyclists. 15 participants were invited to rent electric bicycles as mode of transportation for tourism in and around the small towns Lidköping and Skara for one day. Individual semi structured interviews were performed with the participants. Our main result is that there are aspects of electric bikes that make them particularly appropriate as a sustainable mode of transportation for local tourist destinations, and could also lower the threshold for more sustainable behaviours. Travelling by electric bike was experienced as beneficial in several ways; it automatically and effortlessly gives the cyclist access to nature, it constitutes a plausible option for more sustainable transportation at medium distances, and it allows the entire group of travellers, such as a families, to feel as being part of shaping the journey which contributes to engagement and motivation. Although intended for tourists, it also facilitate local people to access and reflect on their local flora and fauna. We also found that digital tools such as maps, information sources, and booking systems have a key part in the deployment when appropriately integrated. In addition, we found that it was important to lower the threshold of trying electric bikes, and an important key for this was personal service from proficient people who could provide a sense of security by giving instructions, answering questions, and support in adjusting the equipment.

Human-robot interaction (HRI) is fundamentally concerned with studying the interaction between humans and robots. While it is still a relatively young field, it can draw inspiration from other disciplines studying human interaction with other types of agents. Often, such inspiration is sought from the study of human-computer interaction (HCI) and the social sciences studying human-human interaction (HHI). More rarely, the field also turns to human-animal interaction (HAI).

In this paper, we identify two distinct underlying motivations for making such comparisons: to form a target to recreate orto obtain a benchmark (or baseline) for evaluation. We further highlight relevant (existing) overlap between HRI and HAI, and identify specific themes that are of particular interest for further trans-disciplinary exploration. At the same time, since robots and animals are clearly not the same, we also discuss important differences between HRI and HAI, their complementarity notwithstanding. The overall purpose of this discussion is thus to create an awareness of the potential mutual benefit between the two disciplines and to describe opportunities that exist for future work, both in terms of new domains to explore, and existing results to learn from.

The traffic domain is increasingly inhabited by vehicles with driving support systems and automation to the degree where the idea of fully autonomous vehicles is gaining popularity as a credible prediction about the near future. As more aspects of driving become automated, the role of the driver, and the way they perceive their vehicle, surroundings, and fellow road users, change. To address some of the emerging kinds of interaction between different agents in the traffic environment, it is important to take social phenomena and abilities into account, even to the extent of considering highly automated vehicles to be social agents in their own right. To benefit from that, it is important to frame the perception of the traffic environment, as well as the road users in it, in an appropriate theoretical context. We propose that there are helpful concepts related to functional and subjective perception, derived from gestalt psychology and Umweltlehre, that can fill this theoretical need, and support better understanding of vehicles of various degrees of automation.

The term ‘multimodality’ has come to take on several somewhat different meanings depending on the underlying theoretical paradigms and traditions, and the purpose and context of use. The term is closely related to embodiment, which in turn is also used in several different ways. In this paper, we elaborate on this connection and propose that a pragmatic and pluralistic stance is appropriate for multimodality. We further propose a distinction between first and second order effects of multimodality; what is achieved by multiple modalities in isolation and the opportunities that emerge when several modalities are entangled. This highlights questions regarding ways to cluster or interchange different modalities, for example through redundancy or degeneracy. Apart from discussing multimodality with respect to an individual agent, we further look to more distributed agents and situations where social aspects become relevant.

In robotics, understanding the various uses and interpretations of these terms can prevent miscommunication when designing robots, as well as increase awareness of the underlying theoretical concepts. Given the complexity of the different ways in which multimodality is relevant in social robotics, this can provide the basis for negotiating appropriate meanings of the term at a case by case basis.

The rapid spread of antibiotic resistance - currently one of the greatest threats to human health according to WHO - is to a large extent enabled by plasmid-mediated horizontal transfer of resistance genes. Rapid identification and characterization of plasmids is thus important both for individual clinical outcomes and for epidemiological monitoring of antibiotic resistance. Toward this aim, we have developed an optical DNA mapping procedure where individual intact plasmids are elongated within nanofluidic channels and visualized through fluorescence microscopy, yielding barcodes that reflect the underlying sequence. The assay rapidly identifies plasmids through statistical comparisons with barcodes based on publicly available sequence repositories and also enables detection of structural variations. Since the assay yields holistic sequence information for individual intact plasmids, it is an ideal complement to next generation sequencing efforts which involve reassembly of sequence reads from fragmented DNA molecules. The assay should be applicable in microbiology labs around the world in applications ranging from fundamental plasmid biology to clinical epidemiology and diagnostics.

Enjoyment is a crucial yet complex indicator of positive user experience in Human-Robot Interaction (HRI). While manual enjoyment annotation is feasible, developing reliable automatic detection methods remains a challenge. This paper investigates a multimodal approach to automatic enjoyment annotation for HRI conversations, leveraging large language models (LLMs), visual, audio, and temporal cues. Our findings demonstrate that both text-only and multimodal LLMs with carefully designed prompts can achieve performance comparable to human annotators in detecting user enjoyment. Furthermore, results reveal a stronger alignment between LLM-based annotations and user self-reports of enjoyment compared to human annotators. While multimodal supervised learning techniques did not improve all of our performance metrics, they could successfully replicate human annotators and highlighted the importance of visual and audio cues in detecting subtle shifts in enjoyment. This research demonstrates the potential of LLMs for real-time enjoyment detection, paving the way for adaptive companion robots that can dynamically enhance user experiences.

There is a risk of genuine but norm-breaking phenomena related to human-robot interaction remaining invisible, since their rarity make observed instances dismissed as anecdotes. In this extended abstract we present observations related to bias in who is understood in vocal interactions with robots. Noting the fundamentally political and intersectional nature of the problem, we call for a strategy for documenting such comparatively rare or messy events to break the invisibility and facilitate accumulation of evidence.

The Negative Attitude toward Robots Scale (NARS) is one of the most common questionnaires used in the studies of human-robot interaction (HRI). It was established in 2004, and has since then been used in several domains to measure attitudes, both as main results and as a potential confounding factor. To better understand this important tool of HRI research, we reviewed the HRI literature with a specific focus on practice and reporting related to NARS. We found that the use of NARS is being increasingly reported, and that there is a large variation in how NARS is applied. The reporting is, however, often not done in sufficient detail, meaning that NARS results are often difficult to interpret, and comparing between studies or performing meta-analyses are even more difficult. After providing an overview of the current state of NARS in HRI, we conclude with reflections and recommendations on the practices and reporting of NARS.

The aim of this extended abstract is to discuss how speech and voice in robots could impact user expectations, and how we, within the human-robot interaction (HRI) research community, ought to handle human-like speech both in research and in the development of robots. Human-like speech refers to both emotions that are expressed through speech and the synthetic voice profile by the robot. The latter is especially important as artificial human-like speech is becoming indistinguishable from actual human speech. Together, these characteristics may cause certain expectations of what the robot is and what it is capable of which may impact both the immediate interactions between a user and robot, as well as a user's future interactions with robots. While there are many ethical considerations around robot designs, we focus specifically on the ethical implications of speech design choices as these choices affect user expectations. We believe this particular dimension is of importance because it not only effects the user immediately, but also the field of HRI, both as a field of research and design. The stance on deception may vary across the different domains that robots are used within; for example, there is a wider acknowledgment of deception in scientific research compared to commercial use of robots. Some of this variation may turn on technical definitions of deception for specific areas or cases. In this paper, we will take on a more general understanding of deception as an attempt to distort or withhold facts with the aim to mislead.

This paper presents a large-scale simulator study on driver adherence to recommendationsgiven by driver support systems, specifically eco-driving support and navigation support.123 participants took part in this study, and drove a vehicle simulator through a pre-defined environment for a duration of approximately 10 min. Depending on the experi-mental condition, participants were either given no eco-driving recommendations, or asystem whose provided support was either basic (recommendations were given in theform of an icon displayed in a manner that simulates a heads-up display) or informative(the system additionally displayed a line of text justifying its recommendations). A naviga-tion system that likewise provided either basic or informative support, depending on thecondition, was also provided.

Effects are measured in terms of estimated simulated fuel savings as well as engine brak-ing/coasting behaviour and gear change efficiency. Results indicate improvements in allvariables. In particular, participants who had the support of an eco-driving system spenta significantly higher proportion of the time coasting. Participants also changed gears atlower engine RPM when using an eco-driving support system, and significantly more sowhen the system provided justifications. Overall, the results support the notion that pro-viding reasons why a support system puts forward a certain recommendation improvesadherence to it over mere presentation of the recommendation.

Finally, results indicate that participants’ driving style was less eco-friendly if the navi-gation system provided justifications but the eco-system did not. This may be due to par-ticipants considering the two systems as one whole rather than separate entities withindividual merits. This has implications for how to design and evaluate a given driver sup-port system since its effectiveness may depend on the performance of other systems in thevehicle.

When deploying robots, its physical characteristics, role, and tasks are often fixed. Such factors can also be associated with gender stereotypes among humans, which then transfer to the robots. One factor that can induce gendering but is comparatively easy to change is the robot’s voice. Designing voice in a way that interferes with fixed factors might therefore be a way to reduce gender stereotypes in human-robot interaction contexts. To this end, we have conducted a video-based online study to investigate how factors that might inspire gendering of a robot interact. In particular, we investigated how giving the robot a gender-ambiguous voice can affect perception of the robot. We compared assessments (n=111) of videos in which a robot’s body presentation and occupation mis/matched with human gender stereotypes. We found evidence that a gender-ambiguous voice can reduce gendering of a robot endowed with stereotypically feminine or masculine attributes. The results can inform more just robot design while opening new questions regarding the phenomenon of robot gendering.

Recent work identified a concerning trend of disproportional gender representation in research participants in Human-Computer Interaction (HCI). Motivated by the fact that Human-Robot Interaction (HRI) shares many participant practices with HCI, we explored whether this trend is mirrored in our field. By producing a dataset covering participant gender representation in all 684 full papers published at the HRI conference from 2006-2021, we identify current trends in HRI research participation. We find an over-representation of men in research participants to date, as well as inconsistent and/or incomplete gender reporting which typically engages in a binary treatment of gender at odds with published best practice guidelines. We further examine if and how participant gender has been considered in user studies to date, in-line with current discourse surrounding the importance and/or potential risks of gender based analyses. Finally, we complement this with a survey of HRI researchers to examine correlations between the who is doing with the who is taking part, to further reflect on factors which seemingly influence gender bias in research participation across different sub-fields of HRI. Through our analysis we identify areas for improvement, but also reason for optimism, and derive some practical suggestions for HRI researchers going forward.