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A Survey of Behavioral Models for Social Robots

Olivia Nocentini, Laura Fiorini, Giorgia Acerbi, Alessandra Sorrentino, Gianmaria Mancioppi, Filippo Cavallo

Year
2019
Citations
100
Access
Open access

Abstract

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.

Keywords

RobotHuman–computer interactionComputer scienceEmpathyField (mathematics)ScopusCognitionHuman–robot interactionData scienceArtificial intelligence

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