scholarly journals Detecting Lies is a Child (Robot)’s Play: Gaze-Based Lie Detection in HRI

Author(s):  
Dario Pasquali ◽  
Jonas Gonzalez-Billandon ◽  
Alexander Mois Aroyo ◽  
Giulio Sandini ◽  
Alessandra Sciutti ◽  
...  

AbstractRobots destined to tasks like teaching or caregiving have to build a long-lasting social rapport with their human partners. This requires, from the robot side, to be capable of assessing whether the partner is trustworthy. To this aim a robot should be able to assess whether someone is lying or not, while preserving the pleasantness of the social interaction. We present an approach to promptly detect lies based on the pupil dilation, as intrinsic marker of the lie-associated cognitive load that can be applied in an ecological human–robot interaction, autonomously led by a robot. We demonstrated the validity of the approach with an experiment, in which the iCub humanoid robot engages the human partner by playing the role of a magician in a card game and detects in real-time the partner deceptive behavior. On top of that, we show how the robot can leverage on the gained knowledge about the deceptive behavior of each human partner, to better detect subsequent lies of that individual. Also, we explore whether machine learning models could improve lie detection performances for both known individuals (within-participants) over multiple interaction with the same partner, and with novel partners (between-participant). The proposed setup, interaction and models enable iCub to understand when its partners are lying, which is a fundamental skill for evaluating their trustworthiness and hence improving social human–robot interaction.

Philosophies ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 11 ◽  
Author(s):  
Frank Förster

In this article, I assess an existing language acquisition architecture, which was deployed in linguistically unconstrained human–robot interaction, together with experimental design decisions with regard to their enactivist credentials. Despite initial scepticism with respect to enactivism’s applicability to the social domain, the introduction of the notion of participatory sense-making in the more recent enactive literature extends the framework’s reach to encompass this domain. With some exceptions, both our architecture and form of experimentation appear to be largely compatible with enactivist tenets. I analyse the architecture and design decisions along the five enactivist core themes of autonomy, embodiment, emergence, sense-making, and experience, and discuss the role of affect due to its central role within our acquisition experiments. In conclusion, I join some enactivists in demanding that interaction is taken seriously as an irreducible and independent subject of scientific investigation, and go further by hypothesising its potential value to machine learning.


2014 ◽  
Vol 11 (01) ◽  
pp. 1450003 ◽  
Author(s):  
Hatice Kose ◽  
Neziha Akalin ◽  
Pinar Uluer

This paper investigates the role of interaction and communication kinesics in human–robot interaction. This study is part of a novel research project on sign language (SL) tutoring through interaction games with humanoid robots. The main goal is to motivate the children with communication problems to understand and imitate the signs implemented by the robot using basic upper torso gestures and sound. We present an empirical and exploratory study investigating the effect of basic nonverbal gestures consisting of hand movements, body and face gestures expressed by a humanoid robot, and having comprehended the word, the participants will give relevant feedback in SL. This way the participant is both a passive observer and an active imitator throughout the learning process in different phases of the game. A five-fingered R3 robot platform and a three-fingered Nao H-25 robot are employed within the games. Vision-, sound-, touch- and motion-based cues are used for multimodal communication between the robot, child and therapist/parent within the study. This paper presents the preliminary results of the proposed game tested with adult participants. The aim is to evaluate the SL learning ability of participants from a robot, and compare different robot platforms within this setup.


Author(s):  
Stephane Lallee ◽  
Vasiliki Vouloutsi ◽  
Maria Blancas Munoz ◽  
Klaudia Grechuta ◽  
Jordi-Ysard Puigbo Llobet ◽  
...  

AbstractFuture applications of robotic technologies will involve interactions with non-expert humans as machines will assume the role of companions, teachers or healthcare assistants. In all those tasks social behavior is a key ability that needs to be systematically investigated and modelled at the lowest level, as even a minor inconsistency of the robot’s behavior can greatly affect the way humans will perceive it and react to it. Here we propose an integrated architecture for generating a socially competent robot.We validate our architecture using a humanoid robot, demonstrating that gaze, eye contact and utilitarian emotions play an essential role in the psychological validity or social salience of Human-Robot Interaction (HRI). We show that this social salience affects both the empathic bonding between the human and a humanoid robot and, to a certain extent, the attribution of a Theory of Mind (ToM). More specifically, we investigate whether these social cues affect other utilitarian aspects of the interaction such as knowledge transfer within a teaching context.


2020 ◽  
Author(s):  
Agnieszka Wykowska ◽  
Jairo Pérez-Osorio ◽  
Stefan Kopp

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.


2019 ◽  
Author(s):  
Cinzia Di Dio ◽  
Federico Manzi ◽  
Giulia Peretti ◽  
Angelo Cangelosi ◽  
Paul L. Harris ◽  
...  

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.


Author(s):  
Giorgio Metta

This chapter outlines a number of research lines that, starting from the observation of nature, attempt to mimic human behavior in humanoid robots. Humanoid robotics is one of the most exciting proving grounds for the development of biologically inspired hardware and software—machines that try to recreate billions of years of evolution with some of the abilities and characteristics of living beings. Humanoids could be especially useful for their ability to “live” in human-populated environments, occupying the same physical space as people and using tools that have been designed for people. Natural human–robot interaction is also an important facet of humanoid research. Finally, learning and adapting from experience, the hallmark of human intelligence, may require some approximation to the human body in order to attain similar capacities to humans. This chapter focuses particularly on compliant actuation, soft robotics, biomimetic robot vision, robot touch, and brain-inspired motor control in the context of the iCub humanoid robot.


Author(s):  
Margot M. E. Neggers ◽  
Raymond H. Cuijpers ◽  
Peter A. M. Ruijten ◽  
Wijnand A. IJsselsteijn

AbstractAutonomous mobile robots that operate in environments with people are expected to be able to deal with human proxemics and social distances. Previous research investigated how robots can approach persons or how to implement human-aware navigation algorithms. However, experimental research on how robots can avoid a person in a comfortable way is largely missing. The aim of the current work is to experimentally determine the shape and size of personal space of a human passed by a robot. In two studies, both a humanoid as well as a non-humanoid robot were used to pass a person at different sides and distances, after which they were asked to rate their perceived comfort. As expected, perceived comfort increases with distance. However, the shape was not circular: passing at the back of a person is more uncomfortable compared to passing at the front, especially in the case of the humanoid robot. These results give us more insight into the shape and size of personal space in human–robot interaction. Furthermore, they can serve as necessary input to human-aware navigation algorithms for autonomous mobile robots in which human comfort is traded off with efficiency goals.


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.


2020 ◽  
Vol 12 (1) ◽  
pp. 58-73
Author(s):  
Sofia Thunberg ◽  
Tom Ziemke

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.


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