Intuitive human robot interaction based on unintentional synchrony: A psycho-experimental study

Hasnain, Syed K.; Mostafaoui, Ghilès; Salesse, Robin N.; Marín, Ludovic; Gaussier, Philippe

doi:10.1109/devlrn.2013.6652569

Cited by 12 publications

(11 citation statements)

References 39 publications

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“…For example, as referred in [7] "people tend to synchronise their rhythms and movements ... within a conversation". In HRI, it can facilitate the natural interaction with robots with minimal cognitive load [8]. Starting from this knowledge, the features listed below are extracted from the recorded depth videos:…”

Section: Non-verbal Features Extractionmentioning

confidence: 99%

Predicting Extraversion from Non-verbal Features During a Face-to-Face Human-Robot Interaction

Rahbar

Anzalone²,

Varni

et al. 2015

Social Robotics

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Abstract. In this paper we present a system for automatic prediction of extraversion during the first thin slices of human-robot interaction (HRI). This work is based on the hypothesis that personality traits and attitude towards robot appear in the behavioural response of humans during HRI. We propose a set of four non-verbal movement features that characterize human behavior during interaction. We focus our study on predicting Extraversion using these features, extracted from a dataset consisting of 39 healthy adults interacting with the humanoid iCub. Our analysis shows that it is possible to predict to a good level (64%) the Extraversion of a human from a thin slice of interaction relying only on non-verbal movement features. Our results are comparable to the state-of-the-art obtained in HHI [23].

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Section: Non-verbal Features Extractionmentioning

confidence: 99%

Predicting Extraversion from Non-verbal Features During a Face-to-Face Human-Robot Interaction

Rahbar

Anzalone²,

Varni

et al. 2015

Social Robotics

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show abstract

“…Recently, synchrony started to be investigated in HRI. For example, [32] showed that it can facilitate the natural interaction with robots decreasing the cognitive load of the human partner. Basically, at the present, synchrony was explored in the following three ways: movement synchrony, synchrony of direction (that is opposite direction or same direction), and synchrony towards a specific target (e.g., object, person or location).…”

Section: Nonverbal Behavioral Featuresmentioning

confidence: 99%

Automated Prediction of Extraversion During Human–Humanoid Interaction

Anzalone

Varni

Ivaldi

et al. 2017

Int J of Soc Robotics

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One of the most important challenges in ro-botics is to achieve natural and engaging interactions between humans and robots. Interpersonal interaction, the process by which two or more people exchange information through verbal and nonverbal messages, could be exploited by robots both to establish interaction and to inform about its quality. The production of social signals being influenced by individual factors, such as personality traits, is critical for robots to have personalized models of interaction. This paper focuses on estimating social traits such as human personality from the dynamics of interpersonal interaction. The work was carried out in the framework of the Project EDHHI (Engagement During Human-Humanoid Interaction) which focuses on understanding individual factors influencing joint human-humanoid actions. In particular, this work addresses the automated prediction of the Extraversion trait during a human-humanoid interaction. We show how it is possible to take into account the specificity of Human-Robot Interaction (HRI) scenarios by contextualizing personality through the attitude that participants show towards the robots. This attitude is influenced by the a priori knowledge that people have on social robotics, and their prior anxiety in interacting with them. The proposed model exploits a set of nonverbal features chosen according to literature in Psychology and Personality Computing. These features are adopted to characterize human behaviors and the dynamics of human-robot interaction. Experimental results highlight that it possible to predict Extraversion of the human partner from nonverbal behavior during human-robot interaction with an accuracy of 62%. A higher accuracy, 70%, is obtained from the computational model by explicitly combining the dynamics of interpersonal interaction and the attitude of the participants towards the robots. Results show that 120s are needed to obtain such performance.

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“…Empirical research investigating synchrony as a predictor of rapport, similarity, and approval in interpersonal interactions has also been leveraged in the field of human-robot interaction (HRI) (Kendon, 1970 ; Warner, 1992 ; Tickle-Degnen and Gavett, 2003 ; Hasnain et al, 2013 ; Bartneck et al, 2020b ). Recent developments in robotics include making human-robot interactions reflect synchronous interactions between human dyads (Prepin and Revel, 2007 ; Hasnain et al, 2013 ). For example, the adaptable robotics for interaction analysis (ADRIANA) platform enables a robot to detect movements in human users and synchronize its movements automatically in real-time.…”

Section: Introductionmentioning

confidence: 99%

Who's Leading This Dance?: Theorizing Automatic and Strategic Synchrony in Human-Exoskeleton Interactions

2021

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Wearable robots are an emerging form of technology that allow organizations to combine the strength, precision, and performance of machines with the flexibility, intelligence, and problem-solving abilities of human wearers. Active exoskeletons are a type of wearable robot that gives wearers the ability to effortlessly lift up to 200 lbs., as well as perform other types of physically demanding tasks that would be too strenuous for most humans. Synchronization between exoskeleton suits and wearers is one of the most challenging requirements to operate these technologies effectively. In this conceptual paper, we extend interpersonal adaption theory (IAT) to the exoskeleton context and explicate (a) the antecedents that are most likely to shape synchrony in human-exoskeleton interactions, (b) automatic and strategic synchrony as adaptive behaviors in human-exoskeleton interactions, and (c) outcome variables that are especially important in these processes. Lastly, we offer a discussion of key methodological challenges for measuring synchrony in human-exoskeleton interactions and offer a future research agenda for this important area.

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Intuitive human robot interaction based on unintentional synchrony: A psycho-experimental study

Cited by 12 publications

References 39 publications

Predicting Extraversion from Non-verbal Features During a Face-to-Face Human-Robot Interaction

Predicting Extraversion from Non-verbal Features During a Face-to-Face Human-Robot Interaction

Automated Prediction of Extraversion During Human–Humanoid Interaction

Who's Leading This Dance?: Theorizing Automatic and Strategic Synchrony in Human-Exoskeleton Interactions

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