scholarly journals Robot-Fish Interaction Helps to Trigger Social Buffering in Neon Tetras: The Potential Role of Social Robotics in Treating Anxiety

2021 ◽  
Author(s):  
Donato Romano ◽  
Cesare Stefanini
Keyword(s):  
Preference Test ◽  
Social Robotics ◽  
Social Robots ◽  
Robotic Fish ◽  
Treatment Needs ◽  
Social Stimuli ◽  
Dark Light ◽  
Social Buffering ◽  
Test Tank ◽  
Traditional Approaches

AbstractThe emerging field of social robotics comprises several multidisciplinary applications. Anxiety and stress therapies can greatly benefit by socio-emotional support provided by robots, although the intervention of social robots as effective treatment needs to be fully understood. Herein, Paracheirodon innesi, a social fish species, was used to interact with a robotic fish to understand intrinsic and extrinsic mechanisms causing anxiety, and how social robots can be effectively used as anxiety treatments. In the first experiment we tested the effects of a conspecific-mimicking robot on the fish tendency to swim in the bottom when transferred in a new tank. Here, P. innesi spent a significantly longer time in the upper section of the test tank when the robotic fish was present, clearly indicating a reduction of their state of anxiety due to social stimuli. The second experiment was based on a modification of the dark/light preference test, since many teleost fish are scototactic, preferring dark environments. However, when the robotic fish was placed in the white half of the test tank, P. innesi individuals swam longer in this section otherwise aversive. Social support provided by the robotic fish in both experiments produced a better recovery from anxiety due to social buffering, a phenomenon regulated by specific neural mechanisms. This study provides new insights on the evolution and mechanisms of social buffering to reduce anxiety, as well as on the use of social robots as an alternative to traditional approaches in treating anxiety symptoms.

scholarly journals Reinforcement Learning Approaches in Social Robotics

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1292
Author(s):  
Neziha Akalin ◽  
Amy Loutfi
Keyword(s):  
Reinforcement Learning ◽  
Real World ◽  
Social Robotics ◽  
Research Field ◽  
Social Robots ◽  
Learning Approaches ◽  
Reward Function ◽  
Optimal Behavior ◽  
Learning Challenges ◽  
Starting Point

This article surveys reinforcement learning approaches in social robotics. Reinforcement learning is a framework for decision-making problems in which an agent interacts through trial-and-error with its environment to discover an optimal behavior. Since interaction is a key component in both reinforcement learning and social robotics, it can be a well-suited approach for real-world interactions with physically embodied social robots. The scope of the paper is focused particularly on studies that include social physical robots and real-world human-robot interactions with users. We present a thorough analysis of reinforcement learning approaches in social robotics. In addition to a survey, we categorize existent reinforcement learning approaches based on the used method and the design of the reward mechanisms. Moreover, since communication capability is a prominent feature of social robots, we discuss and group the papers based on the communication medium used for reward formulation. Considering the importance of designing the reward function, we also provide a categorization of the papers based on the nature of the reward. This categorization includes three major themes: interactive reinforcement learning, intrinsically motivated methods, and task performance-driven methods. The benefits and challenges of reinforcement learning in social robotics, evaluation methods of the papers regarding whether or not they use subjective and algorithmic measures, a discussion in the view of real-world reinforcement learning challenges and proposed solutions, the points that remain to be explored, including the approaches that have thus far received less attention is also given in the paper. Thus, this paper aims to become a starting point for researchers interested in using and applying reinforcement learning methods in this particular research field.

Flourishing Isn’t Free: Paying Down Our Moral and Social Debt in Robotic Systems

2020 ◽  
Author(s):  
Shannon Vallor
Keyword(s):  
Social Status ◽  
Risk Mitigation ◽  
Social Robotics ◽  
Status Quo ◽  
Social Robots ◽  
Sociotechnical Systems ◽  
Robotic Systems ◽  
The Past ◽  
The Social

The conversation about social robots and ethics has matured considerably over the years, moving beyond two inadequate poles: superficially utilitarian analyses of ethical ‘risks’ of social robots that fail to question the underlying sociotechnical systems and values driving robotics development, and speculative, empirically unfounded fears of robo-pocalypses that likewise leave those underlying systems and values unexamined and unchallenged. Today our perspective in the field is normatively richer and more empirically grounded. However, there is still work to be done. In the transition from risk-mitigation that accepts the social status quo, to deeper thinking about how to design different worlds in which we might flourish with social robots, we nevertheless have not reckoned with the moral and social debt already accumulated in existing robotics systems and our broader culture of sociotechnical innovation. We relish our creative and philosophical imaginings of a future in which we live well with robots, but without a serious reckoning with the past and present, and the legacies of harm and neglect that must be redressed and repaired in order for those futures to be possible and sustainable. This talk explores those legacies and their accumulated debts, and what it will take to liberate social robotics from them.

scholarly journals Natural language generation for social robotics: opportunities and challenges

2019 ◽  
Vol 374 (1771) ◽  
pp. 20180027 ◽  
Author(s):  
Mary Ellen Foster
Keyword(s):  
Natural Language ◽  
Natural Language Generation ◽  
Research Area ◽  
Social Robotics ◽  
Social Robots ◽  
Human Robot Interaction ◽  
High Quality ◽  
Verbal Expression ◽  
Language Generation ◽  
Face To Face

In the increasingly popular and diverse research area of social robotics, the primary goal is to develop robot agents that exhibit socially intelligent behaviour while interacting in a face-to-face context with human partners. An important aspect of face-to-face social conversation is fluent, flexible linguistic interaction; face-to-face dialogue is both the basic form of human communication and the richest and most flexible, combining unrestricted verbal expression with meaningful non-verbal acts such as gestures and facial displays, along with instantaneous, continuous collaboration between the speaker and the listener. In practice, however, most developers of social robots tend not to use the full possibilities of the unrestricted verbal expression afforded by face-to-face conversation; instead, they generally tend to employ relatively simplistic processes for choosing the words for their robots to say. This contrasts with the work carried out Natural Language Generation (NLG), the field of computational linguistics devoted to the automated production of high-quality linguistic content; while this research area is also an active one, in general most effort in NLG is focused on producing high-quality written text. This article summarizes the state of the art in the two individual research areas of social robotics and natural language generation. It then discusses the reasons why so few current social robots make use of more sophisticated generation techniques. Finally, an approach is proposed to bringing some aspects of NLG into social robotics, concentrating on techniques and tools that are most appropriate to the needs of socially interactive robots. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.

scholarly journals Applications and Trends in Social Robotics

Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 212
Author(s):  
Fernando Alonso Martín ◽  
José Carlos Castillo ◽  
María Malfáz ◽  
Álvaro Castro-González
Keyword(s):  
Quality Of Life ◽  
Social Robotics ◽  
Social Robots

Social robots are intended to coexist with humans and engage in relationships that lead them to a better quality of life [...]

scholarly journals Four-Features Evaluation of Text to Speech Systems for Three Social Robots

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 267
Author(s):  
Fernando Alonso Martin ◽  
María Malfaz ◽  
Álvaro Castro-González ◽  
José Carlos Castillo ◽  
Miguel Ángel Salichs
Keyword(s):  
Comparative Study ◽  
Communication Skills ◽  
Social Robotics ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Text To Speech ◽  
Robot Interaction ◽  
Speech Synthesizer ◽  
Human Voice ◽  
Research Questions

The success of social robotics is directly linked to their ability of interacting with people. Humans possess verbal and non-verbal communication skills, and, therefore, both are essential for social robots to get a natural human–robot interaction. This work focuses on the first of them since the majority of social robots implement an interaction system endowed with verbal capacities. In order to do this implementation, we must equip social robots with an artificial voice system. In robotics, a Text to Speech (TTS) system is the most common speech synthesizer technique. The performance of a speech synthesizer is mainly evaluated by its similarity to the human voice in relation to its intelligibility and expressiveness. In this paper, we present a comparative study of eight off-the-shelf TTS systems used in social robots. In order to carry out the study, 125 participants evaluated the performance of the following TTS systems: Google, Microsoft, Ivona, Loquendo, Espeak, Pico, AT&T, and Nuance. The evaluation was performed after observing videos where a social robot communicates verbally using one TTS system. The participants completed a questionnaire to rate each TTS system in relation to four features: intelligibility, expressiveness, artificiality, and suitability. In this study, four research questions were posed to determine whether it is possible to present a ranking of TTS systems in relation to each evaluated feature, or, on the contrary, there are no significant differences between them. Our study shows that participants found differences between the TTS systems evaluated in terms of intelligibility, expressiveness, and artificiality. The experiments also indicated that there was a relationship between the physical appearance of the robots (embodiment) and the suitability of TTS systems.

Anthropomorphism in Social Robotics: Simondon and the Human in Technology

2020 ◽  
Author(s):  
Juho Rantala
Keyword(s):  
Social Robotics ◽  
Social Robots ◽  
Human Interaction ◽  
The Other ◽  
Complex Phenomenon ◽  
Other Hand ◽  
Practical Research

Anthropomorphism is a complex phenomenon that arises from human interaction with other entities and the environment. The phenomenon is thought to be desirable in social robots, enhancing their functionality and sociality. On the other hand, strict anthropomorphism can limit the possible capabilities of robots. Following Gilbert Simondon’s analysis of technology as inherently human, we can create a philosophical description of the foundation on which to begin studying anthropomorphism and, on the other hand, frame practical research in light of this description, thus leading to a more robust understanding of anthropomorphism as a phenomenon.

The Artificial Nature of Social Robots: A Phenomenological Interpretation of Two Conflicting Tendencies in Human-Robot Interaction

2020 ◽  
Author(s):  
Peter Remmers
Keyword(s):  
Phenomenological Theory ◽  
Social Robotics ◽  
Social Robots ◽  
Human Robot Interaction ◽  
Ontological Category ◽  
Image Perception ◽  
Robot Interaction ◽  
Phenomenological Interpretation ◽  
Artificial Nature

Effects of anthropomorphism or zoomorphism in social robotics motivate two opposing tendencies in the philosophy and ethics of robots: a ‘rational’ tendency that discourages excessive anthropomorphism because it is based on an illusion and a ‘visionary’ tendency that promotes the relational reality of human-robot interaction. I argue for two claims: First, the opposition between these tendencies cannot be resolved and leads to a kind of technological antinomy. Second, we can deal with this antinomy by way of an analogy between our treatment of robots as social interactors and the perception of objects in pictures according to a phenomenological theory of image perception. Following this analogy, human- or animal-likeness in social robots is interpreted neither as a psychological illusion, nor as a relational reality. Instead, robots belong to a special ontological category shaped by perception and interaction, similar to objects in images.

Robotics Has a Race Problem

2019 ◽  
Vol 45 (3) ◽  
pp. 538-560 ◽  
Author(s):  
Robert Sparrow
Keyword(s):  
Humanoid Robots ◽  
Social Robotics ◽  
Social Robots ◽  
Race Politics ◽  
The Social ◽  
Design And Manufacture ◽  
The Relationship ◽  
Race Problem

If people are inclined to attribute race to humanoid robots, as recent research suggests, then designers of social robots confront a difficult choice. Most existing social robots have white surfaces and are therefore, I suggest, likely to be perceived as White, exposing their designers to accusations of racism. However, manufacturing robots that would be perceived as Black, Brown, or Asian risks representing people of these races as slaves, especially given the historical associations between robots and slaves at the very origins of the project of robotics. The only way engineers might avoid this ethical and political dilemma is to design and manufacture robots to which people will struggle to attribute race. Doing so, however, would require rethinking the relationship between robots and “the social,” which sits at the heart of the project of social robotics. Discussion of the race politics of robots is also worthwhile because of the potential it has to generate insights about the politics of artifacts, the relationship between culture and technology, and the responsibilities of engineers.

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’.

On Being a Peer

2013 ◽  
Vol 1 (2) ◽  
pp. 58-68 ◽  
Author(s):  
Lykke Brogaard Bertel ◽  
Dorte Malig Rasmussen
Keyword(s):  
Persuasive Technology ◽  
Social Robotics ◽  
Design Guidelines ◽  
Social Robots ◽  
Social Agents ◽  
Related Research ◽  
Social Actors ◽  
Related Design ◽  
Entertainment Robotics

This paper investigates and discusses the persuasive principles of social actors in relation to other theories of technologies as social agents, particularly within the field of Social Robotics and Persuasive Educational and Entertainment Robotics (PEERs). Based on related research and results from a case study on social robots as persuasive social actors in education an extension of the persuasive principles is proposed and related design guidelines for Persuasive Technology as social actors in teaching are presented.

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