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Evaluating the Engagement with Social Robots

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Abstract

To interact and cooperate with humans in their daily-life activities, robots should exhibit human-like “intelligence”. This skill will substantially emerge from the interconnection of all the algorithms used to ensure cognitive and interaction capabilities. While new robotics technologies allow us to extend such abilities, their evaluation for social interaction is still challenging. The quality of a human–robot interaction can not be reduced to the evaluation of the employed algorithms: we should integrate the engagement information that naturally arises during interaction in response to the robot’s behaviors. In this paper we want to show a practical approach to evaluate the engagement aroused during interactions between humans and social robots. We will introduce a set of metrics useful in direct, face to face scenarios, based on the behaviors analysis of the human partners. We will show how such metrics are useful to assess how the robot is perceived by humans and how this perception changes according to the behaviors shown by the social robot. We discuss experimental results obtained in two human-interaction studies, with the robots Nao and iCub respectively.

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Acknowledgments

This work was supported by the Investissiments d’Avenir program (SMART ANR-11-IDEX-0004-02) through Project EDHHI/SMART, the ANR Project Pramad, and by the European Commission, within the projects CoDyCo (FP7-ICT-2011-9, No. 600716) and and Michelangelo Project (FP7-ICT No.288241).

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Authors and Affiliations

  1. Sorbonne Universités, UPMC Université Paris 06, ISIR UMR7222, Paris, France

    Salvatore M. Anzalone & Mohamed Chetouani

  2. CNRS, Institut des Systèmes Intelligents et de Robotique UMR7222, Paris, France

    Salvatore M. Anzalone & Mohamed Chetouani

  3. ETIS Laboratory, UMR CNRS 8051, The University of Cergy-Pontoise, ENSEA, Cergy-Pontoise, France

    Sofiane Boucenna

  4. Inria, 54600, Villers-lès-Nancy, France

    Serena Ivaldi

  5. Intelligent Autonomous Systems Lab, TU Darmstadt, Darmstadt, Germany

    Serena Ivaldi

  6. Université de Lorraine, Loria, UMR n 7503, 54500, Vanduvre-lès-Nancy, France

    Serena Ivaldi

  7. CNRS, Loria, UMR n 7503, 54500, Vandoeuvre-lès-Nancy, France

    Serena Ivaldi

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  1. Salvatore M. Anzalone
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  2. Sofiane Boucenna
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  4. Mohamed Chetouani
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Correspondence to Salvatore M. Anzalone.

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Anzalone, S.M., Boucenna, S., Ivaldi, S. et al. Evaluating the Engagement with Social Robots. Int J of Soc Robotics 7, 465–478 (2015). https://doi.org/10.1007/s12369-015-0298-7

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