scholarly journals Personalization and Localization in Human-Robot Interaction: A Review of Technical Methods

Robotics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 120
Author(s):  
Mehdi Hellou ◽  
Norina Gasteiger ◽  
Jong Yoon Lim ◽  
Minsu Jang ◽  
Ho Seok Ahn
Keyword(s):  
Artificial Intelligence ◽  
Current Literature ◽  
State Of The Art ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Social Conventions ◽  
Verbal Skills ◽  
Education Industry ◽  
The Social

Personalization and localization are important when developing social robots for different sectors, including education, industry, healthcare or restaurants. This allows for an adjustment of robot behaviors according to the needs, preferences or personality of an individual when referring to personalization or to the social conventions or the culture of a country when referring to localization. However, there are different models that enable personalization and localization presented in the current literature, each with their advantages and drawbacks. This work aims to help researchers in the field of social robotics by reviewing and analyzing different papers in this domain. We specifically focus our review by exploring different robots that employ distinct models for the adaptation of the robot to its environment. Additionally, we study an array of methods used to adapt the nonverbal and verbal skills of social robots, including state-of-the-art techniques in artificial intelligence.

scholarly journals The Fundamental Attribution Error in Human-Robot Interaction: An Experimental Investigation on Attributing Responsibility to a Social Robot for Its Pre-Programmed Behavior

2022 ◽  
Author(s):  
Aike C. Horstmann ◽  
Nicole C. Krämer
Keyword(s):  
Experimental Investigation ◽  
Attribution Theory ◽  
Social Robots ◽  
Social Robot ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Fundamental Attribution Error ◽  
Online Study ◽  
The Social ◽  
Attribution Error

AbstractSince social robots are rapidly advancing and thus increasingly entering people’s everyday environments, interactions with robots also progress. For these interactions to be designed and executed successfully, this study considers insights of attribution theory to explore the circumstances under which people attribute responsibility for the robot’s actions to the robot. In an experimental online study with a 2 × 2 × 2 between-subjects design (N = 394), people read a vignette describing the social robot Pepper either as an assistant or a competitor and its feedback, which was either positive or negative during a subsequently executed quiz, to be generated autonomously by the robot or to be pre-programmed by programmers. Results showed that feedback believed to be autonomous leads to more attributed agency, responsibility, and competence to the robot than feedback believed to be pre-programmed. Moreover, the more agency is ascribed to the robot, the better the evaluation of its sociability and the interaction with it. However, only the valence of the feedback affects the evaluation of the robot’s sociability and the interaction with it directly, which points to the occurrence of a fundamental attribution error.

scholarly journals Social robotics and the modulation of social perception and bias

2019 ◽  
Vol 374 (1771) ◽  
pp. 20180037 ◽  
Author(s):  
Joshua Skewes ◽  
David M. Amodio ◽  
Johanna Seibt
Keyword(s):  
Social Cognition ◽  
Impression Formation ◽  
Psychological Research ◽  
Social Robotics ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Mediated Communication ◽  
Robot Interaction ◽  
The Social ◽  
Identity Based

The field of social robotics offers an unprecedented opportunity to probe the process of impression formation and the effects of identity-based stereotypes (e.g. about gender or race) on social judgements and interactions. We present the concept of fair proxy communication—a form of robot-mediated communication that proceeds in the absence of potentially biasing identity cues—and describe how this application of social robotics may be used to illuminate implicit bias in social cognition and inform novel interventions to reduce bias. We discuss key questions and challenges for the use of robots in research on the social cognition of bias and offer some practical recommendations. We conclude by discussing boundary conditions of this new form of interaction and by raising some ethical concerns about the inclusion of social robots in psychological research and interventions. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.

The “Social” of the Socially Interactive Robot: Rethinking Human-Robot Interaction Through Ethnomethodology

2020 ◽  
Author(s):  
Salla Jarske ◽  
Sanna Raudaskoski ◽  
Kirsikka Kaipainen
Keyword(s):  
Social Interaction ◽  
User Experience ◽  
Moral Obligation ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
The Social ◽  
Normative Practice ◽  
Normative Practices

As social robots project socially interactive skills including speech and gestures, they are in a position to project normative practices that humans ordinarily rely upon in their everyday interactions with each other. Social robots enable experiences that are reducible to interaction as a normative practice, such as a sense of moral obligation to respond to a robot’s greeting. This may have consequences both for the user experience and the design of social robots that are currently overlooked. We propose that theoretical-methodological tools from ethnomethodology should be applied to evaluate and investigate the experiences related to social interaction with social robots.

Shall I trust you? From child human-robot interaction to trusting relationships

2019 ◽  
Author(s):  
Cinzia Di Dio ◽  
Federico Manzi ◽  
Giulia Peretti ◽  
Angelo Cangelosi ◽  
Paul L. Harris ◽  
...  
Keyword(s):  
Behavioral Pattern ◽  
Human Robot Interaction ◽  
School Age Children ◽  
Social Relevance ◽  
Robot Interaction ◽  
Cognitive Correlates ◽  
The Social ◽  
The Relationship

Studying trust within human-robot interaction is of great importance given the social relevance of robotic agents in a variety of contexts. We investigated the acquisition, loss and restoration of trust when preschool and school-age children played with either a human or a humanoid robot in-vivo. The relationship between trust and the quality of attachment relationships, Theory of Mind, and executive function skills was also investigated. No differences were found in children’s trust in the play-partner as a function of agency (human or robot). Nevertheless, 3-years-olds showed a trend toward trusting the human more than the robot, while 7-years-olds displayed the reverse behavioral pattern, thus highlighting the developing interplay between affective and cognitive correlates of trust.

scholarly journals Human-Robot Handshaking: A Review

2021 ◽  
Author(s):  
Vignesh Prasad ◽  
Ruth Stock-Homburg ◽  
Jan Peters
Keyword(s):  
Facial Expressions ◽  
Social Contexts ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Natural Interaction ◽  
Internal Factors ◽  
Verbal Behaviour ◽  
Key Factor ◽  
Physical Touch

AbstractFor some years now, the use of social, anthropomorphic robots in various situations has been on the rise. These are robots developed to interact with humans and are equipped with corresponding extremities. They already support human users in various industries, such as retail, gastronomy, hotels, education and healthcare. During such Human-Robot Interaction (HRI) scenarios, physical touch plays a central role in the various applications of social robots as interactive non-verbal behaviour is a key factor in making the interaction more natural. Shaking hands is a simple, natural interaction used commonly in many social contexts and is seen as a symbol of greeting, farewell and congratulations. In this paper, we take a look at the existing state of Human-Robot Handshaking research, categorise the works based on their focus areas, draw out the major findings of these areas while analysing their pitfalls. We mainly see that some form of synchronisation exists during the different phases of the interaction. In addition to this, we also find that additional factors like gaze, voice facial expressions etc. can affect the perception of a robotic handshake and that internal factors like personality and mood can affect the way in which handshaking behaviours are executed by humans. Based on the findings and insights, we finally discuss possible ways forward for research on such physically interactive behaviours.

scholarly journals Question-aware memory network for multi-hop question answering in human–robot interaction

2021 ◽  
Author(s):  
Xinmeng Li ◽  
Mamoun Alazab ◽  
Qian Li ◽  
Keping Yu ◽  
Quanjun Yin
Keyword(s):  
Question Answering ◽  
State Of The Art ◽  
Human Robot Interaction ◽  
Knowledge Graph ◽  
Robot Interaction ◽  
Natural Language Question ◽  
Memory Network ◽  
The Given ◽  
Fine Tune ◽  
Language Question

AbstractKnowledge graph question answering is an important technology in intelligent human–robot interaction, which aims at automatically giving answer to human natural language question with the given knowledge graph. For the multi-relation question with higher variety and complexity, the tokens of the question have different priority for the triples selection in the reasoning steps. Most existing models take the question as a whole and ignore the priority information in it. To solve this problem, we propose question-aware memory network for multi-hop question answering, named QA2MN, to update the attention on question timely in the reasoning process. In addition, we incorporate graph context information into knowledge graph embedding model to increase the ability to represent entities and relations. We use it to initialize the QA2MN model and fine-tune it in the training process. We evaluate QA2MN on PathQuestion and WorldCup2014, two representative datasets for complex multi-hop question answering. The result demonstrates that QA2MN achieves state-of-the-art Hits@1 accuracy on the two datasets, which validates the effectiveness of our model.

scholarly journals Survey of Emotions in Human–Robot Interactions: Perspectives from Robotic Psychology on 20 Years of Research

2021 ◽  
Author(s):  
Ruth Stock-Homburg
Keyword(s):  
Knowledge Production ◽  
Current Knowledge ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Interdisciplinary Field ◽  
Artificial Emotions ◽  
Art Research ◽  
Research Domain

AbstractKnowledge production within the interdisciplinary field of human–robot interaction (HRI) with social robots has accelerated, despite the continued fragmentation of the research domain. Together, these features make it hard to remain at the forefront of research or assess the collective evidence pertaining to specific areas, such as the role of emotions in HRI. This systematic review of state-of-the-art research into humans’ recognition and responses to artificial emotions of social robots during HRI encompasses the years 2000–2020. In accordance with a stimulus–organism–response framework, the review advances robotic psychology by revealing current knowledge about (1) the generation of artificial robotic emotions (stimulus), (2) human recognition of robotic artificial emotions (organism), and (3) human responses to robotic emotions (response), as well as (4) other contingencies that affect emotions as moderators.

scholarly journals User-centred design of humanoid robots’ communication

2020 ◽  
Vol 12 (1) ◽  
pp. 58-73
Author(s):  
Sofia Thunberg ◽  
Tom Ziemke
Keyword(s):  
Mental Models ◽  
Participatory Design ◽  
Humanoid Robot ◽  
State Of The Art ◽  
Design Method ◽  
Humanoid Robots ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Design Concepts ◽  
Design Ideas

AbstractInteraction between humans and robots will benefit if people have at least a rough mental model of what a robot knows about the world and what it plans to do. But how do we design human-robot interactions to facilitate this? Previous research has shown that one can change people’s mental models of robots by manipulating the robots’ physical appearance. However, this has mostly not been done in a user-centred way, i.e. without a focus on what users need and want. Starting from theories of how humans form and adapt mental models of others, we investigated how the participatory design method, PICTIVE, can be used to generate design ideas about how a humanoid robot could communicate. Five participants went through three phases based on eight scenarios from the state-of-the-art tasks in the RoboCup@Home social robotics competition. The results indicate that participatory design can be a suitable method to generate design concepts for robots’ communication in human-robot interaction.

scholarly journals Reports on the 2014 AAAI Fall Symposium Series

AI Magazine ◽  
2015 ◽  
Vol 36 (3) ◽  
pp. 107-112
Author(s):  
Adam B. Cohen ◽  
Sonia Chernova ◽  
James Giordano ◽  
Frank Guerin ◽  
Kris Hauser ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health Informatics ◽  
Autonomous Robots ◽  
Human Robot Interaction ◽  
Energy Market ◽  
Washington Dc ◽  
Robot Interaction ◽  
Language Access ◽  
Symposium Series ◽  
And Behavior

The AAAI 2014 Fall Symposium Series was held Thursday through Saturday, November 13–15, at the Westin Arlington Gateway in Arlington, Virginia adjacent to Washington, DC. The titles of the seven symposia were Artificial Intelligence for Human-Robot Interaction, Energy Market Prediction, Expanding the Boundaries of Health Informatics Using AI, Knowledge, Skill, and Behavior Transfer in Autonomous Robots, Modeling Changing Perspectives: Reconceptualizing Sensorimotor Experiences, Natural Language Access to Big Data, and The Nature of Humans and Machines: A Multidisciplinary Discourse. The highlights of each symposium are presented in this report.

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