Systematic analysis of video data from different human–robot interaction studies: a categorization of social signals during error situations

Robots will soon enter social environments shared with humans. We need robots that are able to efficiently convey social signals during interactions. At the same time, we need to understand the impact of robots’ behavior on the human brain. For this purpose, human behavioral and neural responses to the robot behavior should be quantified offering feedback on how to improve and adjust robot behavior. Under this premise, our approach is to use methods of experimental psychology and cognitive neuroscience to assess the human’s reception of a robot in human-robot interaction protocols. As an example of this approach, we report an adaptation of a classical paradigm of experimental cognitive psychology to a naturalistic human- robot interaction scenario. We show the feasibility of such an approach with a validation pilot study, which demonstrated that our design yielded a similar pattern of data to what has been previously observed in experiments within the area of cognitive psychology. Our approach allows for addressing specific mechanisms of human cognition that are elicited during human-robot interaction, and thereby, in a longer-term perspective, it will allow for designing robots that are well- attuned to the workings of the human brain.

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A Taxonomy of Social Errors in Human-Robot Interaction

ACM Transactions on Human-Robot Interaction ◽

10.1145/3439720 ◽

2021 ◽

Vol 10 (2) ◽

pp. 1-32

Author(s):

Leimin Tian ◽

Sharon Oviatt

Keyword(s):

Social Relationship ◽

Human Robot Interaction ◽

Social Emotional ◽

Robot Interaction ◽

Systematic Analysis ◽

Emotional Dimension ◽

The Social ◽

In The Wild ◽

Open Question ◽

The Impact

Robotic applications have entered various aspects of our lives, such as health care and educational services. In such Human-robot Interaction (HRI), trust and mutual adaption are established and maintained through a positive social relationship between a user and a robot. This social relationship relies on the perceived competence of a robot on the social-emotional dimension. However, because of technical limitations and user heterogeneity, current HRI is far from error-free, especially when a system leaves controlled lab environments and is applied to in-the-wild conditions. Errors in HRI may either degrade a user’s perception of a robot’s capability in achieving a task (defined as performance errors in this work) or degrade a user’s perception of a robot’s socio-affective competence (defined as social errors in this work). The impact of these errors and effective strategies to handle such an impact remains an open question. We focus on social errors in HRI in this work. In particular, we identify the major attributes of perceived socio-affective competence by reviewing human social interaction studies and HRI error studies. This motivates us to propose a taxonomy of social errors in HRI. We then discuss the impact of social errors situated in three representative HRI scenarios. This article provides foundations for a systematic analysis of the social-emotional dimension of HRI. The proposed taxonomy of social errors encourages the development of user-centered HRI systems, designed to offer positive and adaptive interaction experiences and improved interaction outcomes.

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KASPAR – A Minimally Expressive Humanoid Robot for Human–Robot Interaction Research

Applied Bionics and Biomechanics ◽

10.1155/2009/708594 ◽

2009 ◽

Vol 6 (3-4) ◽

pp. 369-397 ◽

Cited By ~ 92

Author(s):

Kerstin Dautenhahn ◽

Chrystopher L. Nehaniv ◽

Michael L. Walters ◽

Ben Robins ◽

Hatice Kose-Bagci ◽

...

Keyword(s):

Social Interaction ◽

Low Cost ◽

Humanoid Robots ◽

Human Robot Interaction ◽

Developmental Robotics ◽

Robot Interaction ◽

Interaction Studies ◽

Technical Features ◽

Novel Design

This paper provides a comprehensive introduction to the design of the minimally expressive robot KASPAR, which is particularly suitable for human–robot interaction studies. A low-cost design with off-the-shelf components has been used in a novel design inspired from a multi-disciplinary viewpoint, including comics design and Japanese Noh theatre. The design rationale of the robot and its technical features are described in detail. Three research studies will be presented that have been using KASPAR extensively. Firstly, we present its application in robot-assisted play and therapy for children with autism. Secondly, we illustrate its use in human–robot interaction studies investigating the role of interaction kinesics and gestures. Lastly, we describe a study in the field of developmental robotics into computational architectures based on interaction histories for robot ontogeny. The three areas differ in the way as to how the robot is being operated and its role in social interaction scenarios. Each will be introduced briefly and examples of the results will be presented. Reflections on the specific design features of KASPAR that were important in these studies and lessons learnt from these studies concerning the design of humanoid robots for social interaction will also be discussed. An assessment of the robot in terms of utility of the design for human–robot interaction experiments concludes the paper.

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