United States

IEEE RO-MAN 2021

Robots as Mirrors of Human Cognition

**31st IEEE International Conference on Robot & Human Interactive Communication**
 This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.
 
 The conference covers a wide range of topics related to Robot and Human Interactive Communication, involving theories, methodologies, technologies, empirical and experimental studies. Papers related to the study of robotic technology, psychology, cognitive science, artificial intelligence, human factors, ethics and policies, interaction-based robot design and other topics related to human-robot interaction are welcome.
 
 **CONFERENCE THEME:**
 Social, asocial, and antisocial robots
 
 Robots are starting to populate our lives: at work, in our homes, hotels, shops. However, not everybody is comfortable with robots finding a place in society. For example, people may be afraid that robots will replace humans in their jobs. This belief is exacerbated by the media that, on one side, raise expectations of robots’ capabilities, while amplifying fears and worries on the other side.
 
 In the next years, due to the increasing request for interaction with people in social environments, academic research and market analyses predict that robots will become more and more “social”. But, at the same time, robots may incur the risk of being perceived as “asocial” as their pervasiveness in everyday environments may become an obstacle to social interaction between humans. Or they may even be rejected as “antisocial” if researchers do not take care to develop robots that behave according to the customs and habits of the communities where they are expected to operate.
 
 To prevent this from happening, robotic researchers can no longer take the luxury of being mere technicians. They must be capable of addressing all the challenges raised by future robot-populated communities in a multidisciplinary way. They need to share their knowledge with the public to make people aware of what robots really are, what expectations we can have from them, the risks we may incur, and the possible mitigation plans.
 
 While being open to any kind of contribution related to Human-Robot Interactive Communication, the RO-MAN 2022 conference will emphasize these aspects of robotic research. How can we create robots capable of being welcomed as our assistants and companions in society while, at the same time, not being perceived as “asocial” or “antisocial?” How can we create robots perceived as facilitators of the natural development of human beings and communities, rather than obstacles?
 
 Contributions from different disciplines, not exclusively related to technological development, will be welcomed as crucial to pave the way to global acceptance of future robots with an informed attitude.
 
 [![](https://assets.underline.io/uploads/markdown_image/1/image/af259abe105b3791c498ae1552d75710.png)](https://drive.google.com/file/d/18w73BZPB_JVOgcrcdZDqYpEupwVt4CnU/view?usp=sharing)

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IEEE RO-MAN 2022

31st IEEE International Conference on Robot & Human Interactive Communication
This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.

keynote

RO-MAN 2021's theme is trustworthiness and cooperation. We chose this term well before the pandemic put the world on edge and added a new reason for us to question our own personal safety when in the company of others. But what about in the company of social robots? What would cause us to trust, or not trust, them? How do we as researchers create that feeling, that critical component of any relationship? With social robots, it is of course largely in our power to design the physical form, the control code and the interface software to maximize trustworthiness, facilitate cooperation and enhance the quality of human-robot interaction. This theme also touches upon people's expectations and perceptions of robots, as well as other social, cognitive and cultural factors that will influence human-robot interactions. We will have a special session/track on this topic, invite targeted submissions and include plenary speakers who are specialist in this area. We sincerely hope that this focus will help enlighten the design-thinking of all of us as we fabricate and program our own various systems.

To access RO-MAN Virtual 2021, [please register here.](https://ro-man2021.org/registration/)

RO-MAN 2021's theme is trustworthiness and cooperation. We chose this term well before the pandemic put the world on edge and added a new reason for us to question our own personal safety when in the company of others. But what about in the company of social robots? What would cause us to trust, or not trust, them? How do we as researchers create that feeling, that critical component of any relationship? With social robots, it is of course largely in our power to design the physical form, the control code and the interface software to maximize trustworthiness, facilitate cooperation and enhance the quality of human-robot interaction. 

As people interact with robots in social contexts, an important research question is the extent to which individuals will feel comfortable disclosing personal information to robots as a function of robot appearance. Using an online questionnaire, 110 participants indicated a strong preference to disclose personal information to a human counselor regardless of the type of information but that they would also disclose more to a friendly appearing robot and female android, than to a robot judged to lack affect.

Self-Disclosure of Personal Information, Robot Appearance, and Robot Trustworthiness

Many people are forced to eat alone recently. We think robots can be good meal partners and investigate who are more likely to accept robots as eating partners and compare eating with a single robot to eating with multiple robots. The results indicated people who had high frequency of solitary eating had more fun eating with two robots than with one, and vast experience with robots and low frequency of solitary eating related to positive impressions of meal partner robots.

A Survey of Robotics and Emotion: Classifications and Models of Emotional Interaction

In this qualitative study, we address the question of how introducing interaction skills and intelligence to cobots may inhibit or encourage users to use them in their work context. The interviews, performed with 15 individuals working in laboratory settings, gave rise to numerous themes relevant to the design of user-empowering cobot interfaces for individuals with varying technology literacy levels: As “programming may not be for a normal person”, talking to a robot may not be for another. Incorporating the unique interests, fears, personal and domain experience of the end users can contribute to the design and development of cobot interfaces as diverse as their needs, thus maximizing the likelihood of successful integration
across diverse work environments.

Design of Haptic Gestures for Affective Social Signaling through a Cushion Interface

This work examines the role of embodiment and algorithmic personalization in a one-on-one game for participants with cerebral palsy. We find that participants prefer the robot to a screen-based agent, and that personalizing the actions selected through the interaction leads to a more engaging experience.

A robot instructor for the prevention and treatment of Sarcopenia in the aging population: a pilot study

In this work, we propose and evaluate a modular system for
robust and natural speech interaction in challenging acoustical
environments. The system has been integrated and tested in
a realistic HRC scenario in which the acoustic interaction
and efficiency have been evaluated. The developed framework
focuses on decreasing the requirements in terms of signal-tonoise
ratio, providing a methodology to evaluate the naturalness
of the interaction and improvements in efficiency.

A Task Allocation Approach for Human-Robot Collaboration in Product Defects Inspection scenarios

During social interaction, politeness plays a vital role in achieving effective communication. We conducted a between-subject user study with two chatbots where one of the chatbots employs polite triggers, and the other one replies intending to answer the queries. We first analyzed how different personality traits influence the response of individual persons to polite triggers. In addition, we also investigated the effects of polite triggers among different genders and age groups using a cross-sectional analysis.

A novel DMP formulation for global and frame independent spatial scaling in the task space

Extrapolation from low-fidelity design iterations is especially critical in HRI. An initial proposal for low-fidelity to higher fidelity extrapolation is developed using insights from cognitive multimedia learning theory to account for prototype medium as well as cognitive demands. Inspired by Donald Norman, our proposal leverages crowdsourced multi-authored scenarios to create additional evidence within an experimental “stress test.” Evidence for positively moderated emotional effects in text-based AV scenarios as well as for our extrapolation proposal are identified.

Discovering SOCIABLE: Using a Conceptual Model to Evaluate the Legibilityand Effectiveness of Backchannel Cues in an Entertainment Scenario

We conducted two user studies and found that an immersive VR display with a fixed screen using stereoscopic images is an applicable and suitable approach for improving depth perception when controlling a UGV in real-time in obstacle avoidance tasks, whether static or moving. It also helped participants lower their workload levels and led to an enhanced user experience.

Robots as Mirrors of Human Cognition

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Self-Disclosure of Personal Information, Robot Appearance, and Robot Trustworthiness

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