scholarly journals A Survey of Behavioral Models for Social Robots

Robotics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 54 ◽  
Author(s):  
Olivia Nocentini ◽  
Laura Fiorini ◽  
Giorgia Acerbi ◽  
Alessandra Sorrentino ◽  
Gianmaria Mancioppi ◽  
...  

The cooperation between humans and robots is becoming increasingly important in our society. Consequently, there is a growing interest in the development of models that can enhance and enrich the interaction between humans and robots. A key challenge in the Human-Robot Interaction (HRI) field is to provide robots with cognitive and affective capabilities, by developing architectures that let them establish empathetic relationships with users. Over the last several years, multiple models were proposed to face this open-challenge. This work provides a survey of the most relevant attempts/works. In details, it offers an overview of the architectures present in literature focusing on three specific aspects of HRI: the development of adaptive behavioral models, the design of cognitive architectures, and the ability to establish empathy with the user. The research was conducted within two databases: Scopus and Web of Science. Accurate exclusion criteria were applied to screen the 4916 articles found. At the end, 56 articles were selected. For each work, an evaluation of the model is made. Pros and cons of each work are detailed by analyzing the aspects that can be improved to establish an enjoyable interaction between robots and users.

Author(s):  
Olivia Nocentini ◽  
Laura Fiorini ◽  
Giorgia Acerbi ◽  
Alessandra Sorrentino ◽  
Gianmaria Mancioppi ◽  
...  

The cooperation between humans and robots is becoming increasingly important in our society. Consequently, there is a growing interest in the development of models that can enhance the interaction between humans and robots. A key challenge in the Human-Robot Interaction (HRI) field is to provide robots with cognitive and affective capabilities, developing architectures that let them establish empathetic relationships with users. Several models have been proposed in recent years to solve this open-challenge. This work provides a survey of the most relevant attempts/works. In details, it offers an overview of the architectures present in literature focusing on three specific aspects of HRI: the development of adaptive behavioural models, the design of cognitive architectures, and the ability to establish empathy with the user. The research was conducted within two databases: Scopus and Web of Science. Accurate exclusion criteria were applied to screen the 1007 articles found (at the end 30 articles were selected). For each work, an evaluation of the model is made. Pros and cons of each work are detailed by analysing the aspects that can be improved so that an enjoyable interaction between robots and users can be established.


Author(s):  
Vignesh Prasad ◽  
Ruth Stock-Homburg ◽  
Jan Peters

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.


Author(s):  
Ruth Stock-Homburg

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.


2017 ◽  
Vol 14 (130) ◽  
pp. 20170101 ◽  
Author(s):  
M. Calisti ◽  
G. Picardi ◽  
C. Laschi

Soft robotics and its related technologies enable robot abilities in several robotics domains including, but not exclusively related to, manipulation, manufacturing, human–robot interaction and locomotion. Although field applications have emerged for soft manipulation and human–robot interaction, mobile soft robots appear to remain in the research stage, involving the somehow conflictual goals of having a deformable body and exerting forces on the environment to achieve locomotion. This paper aims to provide a reference guide for researchers approaching mobile soft robotics, to describe the underlying principles of soft robot locomotion with its pros and cons, and to envisage applications and further developments for mobile soft robotics.


Author(s):  
Matthias Scheutz ◽  
Paul Schermerhorn

Effective decision-making under real-world conditions can be very difficult as purely rational methods of decision-making are often not feasible or applicable. Psychologists have long hypothesized that humans are able to cope with time and resource limitations by employing affective evaluations rather than rational ones. In this chapter, we present the distributed integrated affect cognition and reflection architecture DIARC for social robots intended for natural human-robot interaction and demonstrate the utility of its human-inspired affect mechanisms for the selection of tasks and goals. Specifically, we show that DIARC incorporates affect mechanisms throughout the architecture, which are based on “evaluation signals” generated in each architectural component to obtain quick and efficient estimates of the state of the component, and illustrate the operation and utility of these mechanisms with examples from human-robot interaction experiments.


2020 ◽  
Vol 32 (1) ◽  
pp. 7-7
Author(s):  
Masahiro Shiomi ◽  
Hidenobu Sumioka ◽  
Hiroshi Ishiguro

As social robot research is advancing, the interaction distance between people and robots is decreasing. Indeed, although we were once required to maintain a certain physical distance from traditional industrial robots for safety, we can now interact with social robots in such a close distance that we can touch them. The physical existence of social robots will be essential to realize natural and acceptable interactions with people in daily environments. Because social robots function in our daily environments, we must design scenarios where robots interact closely with humans by considering various viewpoints. Interactions that involve touching robots influence the changes in the behavior of a person strongly. Therefore, robotics researchers and developers need to design such scenarios carefully. Based on these considerations, this special issue focuses on close human-robot interactions. This special issue on “Human-Robot Interaction in Close Distance” includes a review paper and 11 other interesting papers covering various topics such as social touch interactions, non-verbal behavior design for touch interactions, child-robot interactions including physical contact, conversations with physical interactions, motion copying systems, and mobile human-robot interactions. We thank all the authors and reviewers of the papers and hope this special issue will help readers better understand human-robot interaction in close distance.


Author(s):  
Aike C. Horstmann ◽  
Nicole C. Krämer

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.


2018 ◽  
Author(s):  
Anna Henschel ◽  
Emily S. Cross

A wealth of social psychology studies suggest that moving in synchrony with another person positively influences likeability and prosocial behavior towards that individual. Recently, human-robot interaction (HRI) researchers have started to develop real-time, adaptive synchronous movement algorithms for social robots. However, little is known how socially beneficial synchronous movements with a robot actually are. We predicted that moving in synchrony with a robot would improve its likeability and participants’ social motivation towards it, as measured by the number of questions asked during a free interaction period. Using a between-subjects design, we implemented the synchrony manipulation via a drawing task. Contrary to predictions, we found no evidence that participants who moved in synchrony with the robot rated it as more likeable or asked it more questions. By including validated behavioral and neural measures, future studies can generate a better and more objective estimation of synchrony’s effects on rapport with social robots.


2021 ◽  
Author(s):  
Guy Laban ◽  
Arvid Kappas ◽  
Val Morrison ◽  
Emily S. Cross

One major challenge faced by human-robot interaction (HRI) researchers is replicating and extending new findings, to better understand how short, constrained laboratory manipulations might translate to real-world scenarios. Since interactions with social robots are novel and exciting for many people, one particular concern is the extent to which people's behavioural and emotional engagement with robots might develop from initial interactions with a robot, when a robot's novelty is especially salient, and be sustained over time. The aim of this paper is to introduce a research protocol for a mediated long-term online experiment for testing the extent to which social robots’ cognitive architectures can elicit emotionally rich disclosures and expressions from people to identify their needs and emotional states over time. Moreover, this protocol introduces experimental methods for investigating people's perceptions of a social robot in their natural settings during prolonged and regular interactions, and evaluating how novelty effects on human-robot interactions change over time.


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