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The main topic of our workshop will be robotic applications for wellbeing in the real world, which is strongly in line with the RO-MAN 2023 theme of “Design a New Bridge for H-R-I”, which seeks to address the challenges of developing intelligent robots for human health.Robots are becoming more prevalent in our society for task-oriented goals (e.g., cleaning the house, cooking a meal) and social-oriented interactions such as companionship, assistance, and coaching. We expect robots to share our daily lives in our homes, workplaces, and public spaces. However, most HRI works are limited to lab settings because of several challenges associated with running studies In the real world, such as set-up challenges, ethical concerns, and host availability, leading to research results that are only valid in lab settings but not in real-world scenarios. Also, the publication of in-the-wild experiments is one of the main barriers to the deployment of robots in the real-world since those studies usually involve less participants, and in turn leading to less statistically significant results. Hence, the HRI field should encourage long-term in-the-wild studies with the target population (even with a small sample size), as they provide contextualised results not achievable in online or lab studies (which can include larger sample sizes).

Previous Human-Robot Interaction (HRI) research has recently concentrated on applications that promote mental and physical wellbeing, such as mindfulness training and rehabilitative physical therapy. Robotic coaches for wellbeing are becoming an increasingly relevant line of research, as people have shown increased interest in using digital tools to improve their wellbeing, especially during the COVID-19 pandemic.

Workshop Length : Full Day (Hybrid)

Time & Location : TBD

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Autonomous robot applications are rising. With the new wave in artificial intelligence (AI) powered by machine learning and novel algorithms, more complex robotic systems are being designed to function around humans. In this workshop, experts in the field will share their knowledge concerning the design of Human-Robot Interaction (HRI) systems which support explainability, and their evaluation with human users to gather empirical evidences. The workshop is organized as a highly interactive event, in which participants are encouraged to discuss their research in groups and with the experts.

Workshop Length : Half Day

Time & Location : TBD

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In response to demographic shifts contributing to an older population, limited health and social care budgets and staff shortages in institutionalised care for older adults, caring robots are increasingly imagined as potential caregivers for older adults. During the past 20 years, several initiatives have sought to design, develop, and deploy robots in care environments, focusing on robots assisting with, for example, physical and cognitive training, or providing social companionship. In this workshop we want to focus on the concept of care in the development and use of care robots for older adults. We are interested in: What different understandings of care are at play in care robotics for older adults, which practical implementation factors are there (such as infrastructure, WIFI, staff digital health literacy, investment potential), and how are care robots perceived by different key stakeholders (such as older adults, care staff, family, municipalities/care companies). We want to encourage critical reflection around these questions and invite creative ideas for how to design care robots for older adults.
The aim of this half-day workshop is to provide a forum to share and learn about recent research and experiences with care robotics for older adults. The workshop will be an online event.

Workshop Length : Half Day (Online-only)

Time & Location : TBD

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The proposed workshop aims to provide a cutting-edge perspective on group interactions in the field of Human-Robot Interaction. As social and cognitive robots become increasingly integrated into our daily lives and are introduced into multi-party contexts such as schools, care facilities, and workplaces, it is crucial to ensure that their behavior considers the complex social dynamics present in these scenarios. However, studying group dynamics in HRI entails inherent challenges from both a technical (e.g., tracking multiple users simultaneously) and a theoretical point of view (e.g., modeling multiple agents who dynamically influence each other). New challenges, therefore, await the HRI community, such as ensuring that social robots can adapt to the needs of individual group members while also considering the group as a whole, susceptible to subtle and hidden social norms and balances. Furthermore, it is crucial that robots do not exhibit biases or unethical behavior in these contexts, eventually leading to negative consequences such as social exclusion. One possible approach to overcome these challenges is through experimental designs based on gamification. This approach can favor an unbiased way of behaving in laboratory experiments, mitigating the Hawthorne effect (i.e., the variations in behavior due to the presence of an observer). Participants are invited to share innovative strategies for exploring group-robot interactions, with approaches focused on - but not limited to – gamification, providing a fresh and insightful viewpoint to (1) using social robots for understanding group dynamics; (2) designing social agents able to interact with groups. Additionally, the discussion will involve the ethical implications of researching group dynamics, including potential negative outcomes such as biases toward group members.

Workshop Length : Half Day

Time & Location : TBD

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The importance of personalisation in Human-Robot Interaction has already shown its advantages in multiple scenarios and will become a prevalent direction for the field.
Personalisation has the potential to significantly improve short- and long-term interactions in a variety of real-world scenarios by fostering trust and rapport, increasing adherence to the interaction, increasing engagement through tailored content, and improving task performance.
As a result, deploying robots capable of doing so requires the manufacturers to model reasoning and perceptual capabilities.
However, we need to ponder whether and to what extent personalisation can benefit the interactions, and ultimately the users. Indeed, cultural biases, gender and age stereotypes might be amplified by robots that are developed as end-to-end systems for conducting social interactions. It is therefore of utmost importance to discuss contexts and environments in which personalisation is desired or required for the field and those in which it should be avoided. The contrast occurs between data-driven vs knowledge-driven approaches, in which the first can empower robots with personalisation skills while the latter can be better suited for explaining the decision process of the robot's behaviour.
The workshop focuses on the benefits and drawbacks of personalisation and behavioural adaptation in social HRI.
In particular, this workshop aims at bringing together a multidisciplinary group of researchers from areas including, but not limited to, psychology, neuroscience, computer science, robotics, and sociology, to share and discuss current approaches to empowering social assistive robots with adaptive and learning capabilities in order to foster research and development of robotic solutions specifically designed for meeting the individual's unique needs.

Workshop Length : Half Day(Hybrid)

Time & Location : TBD

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Humans are usually flexible enough to adapt and cope with various situations. A key aspect of this ability is their self-awareness of what wthey know and do not know, which provides a strong foundation for learning. In addition, asking good questions to gain knowledge or resolve uncertainty is a powerful tool for improving personal intellectual ability. On the other hand, robots and artificial intelligence (AI) agents cannot distinguish between what they know and what they do not know, so they do not deal with unlearned or unfamiliar situations. To address this issue, several studies have been conducted in recent years. These studies show that AI agents can respond effectively to unknown situations if they understand the uncertainty and can learn by human interactions, such as asking questions.
This workshop aims to bring together leading experts from diverse fields, including vision, language, and embodied AI, to share their insights on current research trends and engage in meaningful discussions about the future challenges in "Learning by Asking". The workshop will consist of contributed talks, contributed posters, invited talks, and panelist on a wide variety of novel vision and language methods and robot applications

Workshop Length : Half Day

Time & Location : TBD

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Mutual affective understanding is integral for achieving the so-called Theory of Mind (ToM) allowing successful, acceptable and intelligent social human-robot interaction (HRI).
Corresponding concepts rely on new paradigms of robotic control systems that consider not only the possibility for a robot to interpret humans’ observable behaviors and internal/emotional states with the aim of anticipating and adapting to their subsequent reactions, but also to facilitate humans in the interpretation and anticipation of the robot’s state, intentions, and future actions through legible behavior designed around the emotional dimension of the communication. It is crucial to endow a robot with the ability to maintain a model of how human partners perceive the world and the robot itself, so as to be able to understand them better and to generate behaviors that are understandable by them. In addition to being able to detect and interpret humans' basic affective responses so as to adapt their behavior accordingly, robots should also be endowed with the ability to show affective and social responses in a legible way for humans to allow acceptability and efficient human-machine communication. This is especially desirable in the field of Socially and Assistive Robotics (SAR), where interaction often takes place with disabled or vulnerable people. Moreover, robots can help decrease the workload and physical contact of healthcare specialists, which would be beneficial to overcome the situations where elderly or vulnerable people are at risk of getting infected. The need to ensure the positive feelings and acceptance of people, while providing them with the necessary assistance, has outlined the utility of intelligent and empathic socially assistive robots. In these contexts, it is of paramount importance to consider the effect of verbal and non-verbal emotional social cues of the robot on the affective state of the user with whom it is interacting. On the one hand, a robot can be employed to provide assistance to individuals with disability (e.g., cognitive or physical rehabilitation exercises) with the aim of increasing their health and improving their quality of life. On the other hand, its presence and actions could also potentially trigger negative emotions such as stress or discomfort if not tailored to the particular individual’s needs and expectations. This may cause serious difficulties by negatively impacting the users' health and, in turn, achieving a counter-productive result. In this context, robots could use the affect-sensing capability to learn and adapt their behavior to be more comfortable for individuals and to achieve a higher degree of learnability and acceptability through inclusive interaction.
This edition of BAILAR Workshop aims at putting the mutual understanding of affective/emotional states of robots and humans at the crossroads with learning and user adaptation within HRI. Methodologies and technologies adopted for detecting and adapting to users’ mental states, emotions and dispositions during HRI will be presented and discussed. Experimental protocols and results could also outline possible effects of gender, age, personality and pathology on robot perception from an emotional and affective point of view, as well as ethical considerations regarding learning and using personal data within assistive applications.

Workshop Length : Half Day

Time & Location : TBD

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People’s ability of accepting and trusting robots is fundamental for a fruitful and successful coexistence between humans and robots. While advanced progress is made in studying and evaluating the factors affecting people’s acceptance and trust in robots in controlled or short-term (repeated interactions) settings, developing service and personal robots that are accepted and trusted by people still presents an open challenge for scientists in robotics, AI and HRI. In such unstructured static and dynamic human-centred environments scenarios, robots should be able to learn and adapt their behaviours to the situational context, but also to people’s prior experiences and learned associations, their expectations, and their and the robot’s ability to predict and understand each other's behaviours. This workshop focuses on identifying the challenges and dynamics between people and robots to foster short interactions and long-lasting relationships in different fields, from educational, service, collaborative, companion, care-home and medical robotics. Moreover, from previous editions and recent literature, it is also clear that the field of HRI field lacks measures that can effectively and unmistakably assess people’s trust in robots. In this workshop, we also aim to not only produce groundbreaking research to effectively design socially acceptable and trustable robots to be deployed “in the wild”, but also to develop novel methods to assess people’s trust towards them. To this extent, we will organise a spin-date discussion, following the “world café” method, to draft an initial questionnaire to measure the aspects we believe affect the most people’s trust in robots.

Workshop Length : Half Day

Time & Location : TBD

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For human-robot and human-system speech-based communication, various researches have been actively studied, including automatic speech recognition (ASR), natural language processing, dialog management, and speech synthesis, by focussing on communication and/or interaction.
For example, ASR is a key component for natural and smooth human-robot interaction, but there are many obstacles to overcome in the real world, such as noise, interruption, barge-in, latency, and so on. Many techniques based on emerging deep learning technology have been proposed in the speech processing community to address these well-known problems, they have not been technically discussed in the context of human-robot communication, and thus these techniques have limitations to apply them to real human-robot communication scenarios due to lack of robustness and technological unmatch with a target application. This situation tells us the necessity of technical discussion considering application-specific requirements.
The goal of this workshop is to identify real-world challenges and explore their solutions for more practical human-robot and human-system speech-based communication by sharing real-world application-specific problems, which are actually faced by speakers and audience in this workshop.

Workshop Length : Half Day

Time & Location : TBD

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Current industrial robots cannot be programmed or taught in a way equivalent to how human-to-human teaching happens. When a human is teaching another human, the human demonstrates a task via actions and gestures which act on objects towards completing a task. This is unlike current approaches in robotics where robot arms are Kinaesthetically taught. Moreover, after being taught, it is currently difficult for robots to deal with various variations in their environment after they have been programmed to do a task. The aim is that the assembled speakers will provide various viewpoints on the journey to build the next generation of cognitive robots while highlighting the gaps in current approaches.

Workshop Length : Full Day

Time & Location : TBD

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With the progress in numerical healthcare over the past years, the need for numerical tool in the clinical workflow is growing either for pre, per or post-operative steps. This need is amplified by the constant growing use of new imaging tools and robots in Minimally Invasive Surgery (MIS) and radiology. This rapid evolution of surgical tools and techniques put a particular stress on image processing, allowing for instance augmented view, auto segmentation or robotic registration. But when image-based algorithms fail to provide consistent results, the use of numerical models, such as mechanical models, can help to regularize the results. This workshop will present new advances in those two key domains for numerical healthcare: human models for image recognition and numerical models for training and medical robotics.

Workshop Length : Half Day

Time & Location : TBD

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This workshop deals with methodological aspects of the investigation of diversity in human-robot interaction. Especially for application fields in public spaces, the target audience in human-robot interaction varies and robots meet people with a wide range of diversity features. In order to create a human-centered interaction, these features need to be taken into account, as a) robots must be able to interact with any user independent of their individual characteristics and b) it is desirable that the robot can adapt to specific needs in dependence of these individual characteristics. However, there are still various challenges in detecting (cf. algorithmic biases), interacting, and responding to various audiences that need to be addressed in future research considering ethical, technical, and methodological aspects. With this workshop, we like to discuss state-of-the-art challenges, possible solutions, and best practices.

Workshop Length : Half Day(Hybrid)

Time & Location : TBD

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The workshop on Multidisciplinary Perspectives on Context-aware embodied Spoken Interactions (MP-COSIN),proposed to be held at the RO-MAN 2023 conference in Busan, Korea, aims to gather researchers in the fields of speech technology, dialogue systems, and human-robot interaction to discuss the challenges of creating interactive agents that can take their environment, context and own embodiment into account to make the interactions with their users convincing. While spoken interactions with embodied agents already incorporate complicated challenges to deploy systems in the real world, the addition of a dynamically evolving context during the interaction brings higher complexity to this task. As these types of interactions can fail or succeed in many different ways, it is important to bring together different fields to share experiences in addressing this research path. In particular, communities with a history of research on spoken dialogue systems, conversation analysis, and conversational user interfaces can provide a common ground on the notion of context-awareness and how it could be developed for robotics and human-robot interaction.

Workshop Length : Half Day(Hybrid)

Time & Location : TBD

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The research on Artificial Intelligence (AI) in education has seen significant growth in recent years, as educators and researchers explore the potential of this technology to enhance and transform the learning process. Research in this area covers a wide range of topics, including the use of AI for personalized learning, the development of educational games and simulations, and more recently the integration of AI-powered social robots into the classroom. In this 8th edition of the Robots for Learning (R4L) workshop, researchers and educators will be invited to discuss the potential of using AI in their research. Different types of AI will be discussed, looking at their advantages, best practices and potential risks in using AI tools to support robots in educational settings.

Workshop Length : Half Day

Time & Location : TBD

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Nowadays, in either indoor environments or industrial settings, the collaborative tasks between robotic systems and humans have been playing a significant role. This is further boosted by knowledge-driven frameworks, that facilitate robot-robot, human-robot, or human-systems communications. Moreover, machine learning and artificial intelligence tools, together with cognitive automation approaches, data-driven industrial processes, and digital twins might make robotic systems smarter for the new generation of advanced systems. With this perspective, different scientific and technological key issues, tackled by the scientific community for smart manufacturing, will be addressed here. The objective of this workshop is to share expertise and overview scientific issues, current techniques, and achievements in the domains of interaction and collaboration between humans and robots or smart systems. This workshop addresses some key aspects of collaborative settings that improve when using ontology and knowledge representation and reasoning. It provides a platform for practitioners from the various engineering fields meet and match open problems to promising approaches, and review progress in knowledge-enabled robotics. Topics include, but are not limited to knowledge driven approaches supporting: Human-robot interaction; robot-robot collaboration; Human-machine interactions; Natural language processing during interaction; Trustworthy systems; Adaptive manipulation planning; Ontologies-based modeling and reasoning; Dexterous manipulation; Smart manufacturing applications.

Workshop Length : Full Day

Time & Location : TBD

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