Socially Embodied Human-Robot Interaction

2015 ◽  
pp. 169-190 ◽  
Author(s):  
J. Lindblom ◽  
B. Alenljung
Keyword(s):  
User Experience ◽  
Human Robot Interaction ◽  
The Body ◽  
Human Interaction ◽  
Future Research ◽  
Crucial Importance ◽  
Robot Interaction ◽  
Use Of Technology ◽  
Fundamental Challenge ◽  
Socially Interactive Robots

A fundamental challenge of human interaction with socially interactive robots, compared to other interactive products, comes from them being embodied. The embodied nature of social robots questions to what degree humans can interact ‘naturally' with robots, and what impact the interaction quality has on the user experience (UX). UX is fundamentally about emotions that arise and form in humans through the use of technology in a particular situation. This chapter aims to contribute to the field of human-robot interaction (HRI) by addressing, in further detail, the role and relevance of embodied cognition for human social interaction, and consequently what role embodiment can play in HRI, especially for socially interactive robots. Furthermore, some challenges for socially embodied interaction between humans and socially interactive robots are outlined and possible directions for future research are presented. It is concluded that the body is of crucial importance in understanding emotion and cognition in general, and, in particular, for a positive user experience to emerge when interacting with socially interactive robots.

User Experience in Social Human-Robot Interaction

2017 ◽  
Vol 8 (2) ◽  
pp. 12-31 ◽  
Author(s):  
Beatrice Alenljung ◽  
Jessica Lindblom ◽  
Rebecca Andreasson ◽  
Tom Ziemke
Keyword(s):  
User Experience ◽  
Interdisciplinary Research ◽  
Human Robot Interaction ◽  
Added Value ◽  
Future Research ◽  
Human Society ◽  
Research Needs ◽  
Robot Interaction ◽  
Socially Interactive Robots

Socially interactive robots are expected to have an increasing importance in human society. For social robots to provide long-term added value to people's lives, it is of major importance to stress the need for positive user experience (UX) of such robots. The human-centered view emphasizes various aspects that emerge in the interaction between humans and robots. However, a positive UX does not appear by itself but has to be designed for and evaluated systematically. In this paper, the focus is on the role and relevance of UX in human-robot interaction (HRI) and four trends concerning the role and relevance of UX related to socially interactive robots are identified, and three challenges related to its evaluation are also presented. It is argued that current research efforts and directions are not sufficient in HRI research, and that future research needs to further address interdisciplinary research in order to achieve long-term success of socially interactive robots.

User Experience in Social Human-Robot Interaction

2019 ◽  
pp. 1468-1490 ◽  
Author(s):  
Beatrice Alenljung ◽  
Jessica Lindblom ◽  
Rebecca Andreasson ◽  
Tom Ziemke
Keyword(s):  
User Experience ◽  
Interdisciplinary Research ◽  
Human Robot Interaction ◽  
Added Value ◽  
Future Research ◽  
Human Society ◽  
Research Needs ◽  
Robot Interaction ◽  
Socially Interactive Robots

Socially interactive robots are expected to have an increasing importance in human society. For social robots to provide long-term added value to people's lives, it is of major importance to stress the need for positive user experience (UX) of such robots. The human-centered view emphasizes various aspects that emerge in the interaction between humans and robots. However, a positive UX does not appear by itself but has to be designed for and evaluated systematically. In this paper, the focus is on the role and relevance of UX in human-robot interaction (HRI) and four trends concerning the role and relevance of UX related to socially interactive robots are identified, and three challenges related to its evaluation are also presented. It is argued that current research efforts and directions are not sufficient in HRI research, and that future research needs to further address interdisciplinary research in order to achieve long-term success of socially interactive robots.

User Experience of Socially Interactive Robots

2015 ◽  
pp. 352-364 ◽  
Author(s):  
B. Alenljung ◽  
J. Lindblom
Keyword(s):  
Everyday Life ◽  
User Experience ◽  
Human Robot Interaction ◽  
Additional Research ◽  
Wide Spread ◽  
Robot Interaction ◽  
Research Directions ◽  
Research User ◽  
Socially Interactive Robots

Socially interactive robots are expected to have an increasing importance in everyday life for a growing number of people, but negative user experience (UX) can entail reluctance to use robots. Positive user experience underpins proliferation of socially interactive robots. Therefore, it is essential for robot developers to put serious efforts to attain social robots that the users experience as positive. In current human-robot interaction (HRI) research, user experience is reckoned to be important and is used as an argument for stating that something is positive. However, the notion of user experience is noticeably often taken for granted and is neither described nor problematized. By recognizing the complexity of user experience the intended contributions can be even more valuable. Another trend in HRI research is to focus on user experience evaluation and examination of user experience. The current research paths of user experience of socially interactive robots are not enough. This chapter suggests that additional research directions are needed in order accomplish long-term, wide-spread success of socially interactive robots.

scholarly journals “Hmm, Did You Hear What I Just Said?”: Development of a Re-Engagement System for Socially Interactive Robots

Robotics ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 95
Author(s):  
Hoang-Long Cao ◽  
Paola Cecilia Torrico Moron ◽  
Pablo G. Esteban ◽  
Albert De Beir ◽  
Elahe Bagheri ◽  
...  
Keyword(s):  
Human Robot Interaction ◽  
Human Interaction ◽  
User Engagement ◽  
Affective States ◽  
Robot Interaction ◽  
Usability Test ◽  
Socially Interactive Robots ◽  
Technical Operation ◽  
Engagement System ◽  
Attention Level

Maintaining engagement is challenging in human–human interaction. When disengagements happen, people try to adapt their behavior with an expectation that engagement will be regained. In human–robot interaction, although socially interactive robots are engaging, people can easily drop engagement while interacting with robots. This paper proposes a multi-layer re-engagement system that applies different strategies through human-like verbal and non-verbal behaviors to regain user engagement, taking into account the user’s attention level and affective states. We conducted a usability test in a robot storytelling scenario to demonstrate technical operation of the system as well as to investigate how people react when interacting with a robot with re-engagement ability. Our usability test results reveal that the system has the potential to maintain a user’s engagement. Our selected users gave positive comments, through open-ended questions, to the robot with this ability. They also rated the robot with the re-engagement ability higher on several dimensions, i.e., animacy, likability, and perceived intelligence.

scholarly journals The Development of Overtrust: An Empirical Simulation and Psychological Analysis in the Context of Human–Robot Interaction

2021 ◽  
Vol 8 ◽  
Author(s):  
Daniel Ullrich ◽  
Andreas Butz ◽  
Sarah Diefenbach
Keyword(s):  
Well Being ◽  
Repeated Measurements ◽  
Human Robot Interaction ◽  
Human Interaction ◽  
Future Research ◽  
Robot Interaction ◽  
Design Decisions ◽  
Psychological Analysis ◽  
Dissonance Theory ◽  
Important Basis

With impressive developments in human–robot interaction it may seem that technology can do anything. Especially in the domain of social robots which suggest to be much more than programmed machines because of their anthropomorphic shape, people may overtrust the robot's actual capabilities and its reliability. This presents a serious problem, especially when personal well-being might be at stake. Hence, insights about the development and influencing factors of overtrust in robots may form an important basis for countermeasures and sensible design decisions. An empirical study [N = 110] explored the development of overtrust using the example of a pet feeding robot. A 2 × 2 experimental design and repeated measurements contrasted the effect of one's own experience, skill demonstration, and reputation through experience reports of others. The experiment was realized in a video environment where the participants had to imagine they were going on a four-week safari trip and leaving their beloved cat at home, making use of a pet feeding robot. Every day, the participants had to make a choice: go to a day safari without calling options (risk and reward) or make a boring car trip to another village to check if the feeding was successful and activate an emergency call if not (safe and no reward). In parallel to cases of overtrust in other domains (e.g., autopilot), the feeding robot performed flawlessly most of the time until in the fourth week; it performed faultily on three consecutive days, resulting in the cat's death if the participants had decided to go for the day safari on these days. As expected, with repeated positive experience about the robot's reliability on feeding the cat, trust levels rapidly increased and the number of control calls decreased. Compared to one's own experience, skill demonstration and reputation were largely neglected or only had a temporary effect. We integrate these findings in a conceptual model of (over)trust over time and connect these to related psychological concepts such as positivism, instant rewards, inappropriate generalization, wishful thinking, dissonance theory, and social concepts from human–human interaction. Limitations of the present study as well as implications for robot design and future research are discussed.

The role and relationship of mindreading and social attunement in HRI – position statements of interdisciplinary researchers. Workshop HRI'20

2020 ◽  
Author(s):  
Agnieszka Wykowska ◽  
Jairo Pérez-Osorio ◽  
Stefan Kopp
Keyword(s):  
Mental States ◽  
Human Robot Interaction ◽  
Human Interaction ◽  
Artificial Agents ◽  
The Novel ◽  
Robot Interaction ◽  
Novel Coronavirus ◽  
Relationship Of ◽  
The Relationship

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.

scholarly journals Should my robot know what's best for me? Human–robot interaction between user experience and ethical design

AI & Society ◽  
2021 ◽  
Author(s):  
Nora Fronemann ◽  
Kathrin Pollmann ◽  
Wulf Loh
Keyword(s):  
User Experience ◽  
Interaction Design ◽  
Real Life ◽  
Well Being ◽  
Design Principles ◽  
Human Robot Interaction ◽  
Ethical Challenges ◽  
Original Design ◽  
Robot Interaction ◽  
Ethical Design

AbstractTo integrate social robots in real-life contexts, it is crucial that they are accepted by the users. Acceptance is not only related to the functionality of the robot but also strongly depends on how the user experiences the interaction. Established design principles from usability and user experience research can be applied to the realm of human–robot interaction, to design robot behavior for the comfort and well-being of the user. Focusing the design on these aspects alone, however, comes with certain ethical challenges, especially regarding the user’s privacy and autonomy. Based on an example scenario of human–robot interaction in elder care, this paper discusses how established design principles can be used in social robotic design. It then juxtaposes these with ethical considerations such as privacy and user autonomy. Combining user experience and ethical perspectives, we propose adjustments to the original design principles and canvass our own design recommendations for a positive and ethically acceptable social human–robot interaction design. In doing so, we show that positive user experience and ethical design may be sometimes at odds, but can be reconciled in many cases, if designers are willing to adjust and amend time-tested design principles.

scholarly journals Improving Human–Robot Interaction by Enhancing NAO Robot Awareness of Human Facial Expression

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6438
Author(s):  
Chiara Filippini ◽  
David Perpetuini ◽  
Daniela Cardone ◽  
Arcangelo Merla
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Facial Expression Recognition ◽  
Affective Computing ◽  
Human Robot Interaction ◽  
Human Interaction ◽  
Expression Recognition ◽  
Robot Interaction ◽  
Interaction Field ◽  
Nao Robot

An intriguing challenge in the human–robot interaction field is the prospect of endowing robots with emotional intelligence to make the interaction more genuine, intuitive, and natural. A crucial aspect in achieving this goal is the robot’s capability to infer and interpret human emotions. Thanks to its design and open programming platform, the NAO humanoid robot is one of the most widely used agents for human interaction. As with person-to-person communication, facial expressions are the privileged channel for recognizing the interlocutor’s emotional expressions. Although NAO is equipped with a facial expression recognition module, specific use cases may require additional features and affective computing capabilities that are not currently available. This study proposes a highly accurate convolutional-neural-network-based facial expression recognition model that is able to further enhance the NAO robot’ awareness of human facial expressions and provide the robot with an interlocutor’s arousal level detection capability. Indeed, the model tested during human–robot interactions was 91% and 90% accurate in recognizing happy and sad facial expressions, respectively; 75% accurate in recognizing surprised and scared expressions; and less accurate in recognizing neutral and angry expressions. Finally, the model was successfully integrated into the NAO SDK, thus allowing for high-performing facial expression classification with an inference time of 0.34 ± 0.04 s.

scholarly journals Brain activity during reciprocal social interaction investigated using conversational robots as control condition

2019 ◽  
Vol 374 (1771) ◽  
pp. 20180033 ◽  
Author(s):  
Birgit Rauchbauer ◽  
Bruno Nazarian ◽  
Morgane Bourhis ◽  
Magalie Ochs ◽  
Laurent Prévot ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Social Interaction ◽  
Medial Prefrontal Cortex ◽  
Brain Activity ◽  
Blood Oxygen Level Dependent ◽  
Human Robot Interaction ◽  
Human Interaction ◽  
Peripheral Blood Flow ◽  
Robot Interaction ◽  
Temporoparietal Junction

We present a novel functional magnetic resonance imaging paradigm for second-person neuroscience. The paradigm compares a human social interaction (human–human interaction, HHI) to an interaction with a conversational robot (human–robot interaction, HRI). The social interaction consists of 1 min blocks of live bidirectional discussion between the scanned participant and the human or robot agent. A final sample of 21 participants is included in the corpus comprising physiological (blood oxygen level-dependent, respiration and peripheral blood flow) and behavioural (recorded speech from all interlocutors, eye tracking from the scanned participant, face recording of the human and robot agents) data. Here, we present the first analysis of this corpus, contrasting neural activity between HHI and HRI. We hypothesized that independently of differences in behaviour between interactions with the human and robot agent, neural markers of mentalizing (temporoparietal junction (TPJ) and medial prefrontal cortex) and social motivation (hypothalamus and amygdala) would only be active in HHI. Results confirmed significantly increased response associated with HHI in the TPJ, hypothalamus and amygdala, but not in the medial prefrontal cortex. Future analysis of this corpus will include fine-grained characterization of verbal and non-verbal behaviours recorded during the interaction to investigate their neural correlates. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction'.

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