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If You Are Careful, So Am I! How Robot Communicative Motions Can Influence Human Approach in a Joint Task

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Social Robotics (ICSR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13817))

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Abstract

As humans, we have a remarkable capacity for reading the characteristics of objects only by observing how another person carries them. Indeed, how we perform our actions naturally embeds information on the item features. Collaborative robots can achieve the same ability by modulating the strategy used to transport objects with their end-effector. A contribution in this sense would promote spontaneous interactions by making an implicit yet effective communication channel available. This work investigates if humans correctly perceive the implicit information shared by a robotic manipulator through its movements during a dyadic collaboration task. Exploiting a generative approach, we designed robot actions to convey virtual properties of the transported objects, particularly to inform the partner if any caution is required to handle the carried item. We found that carefulness is correctly interpreted when observed through the robot movements. In the experiment, we used identical empty plastic cups; nevertheless, participants approached them differently depending on the attitude shown by the robot: humans change how they reach for the object, being more careful whenever the robot does the same. This emerging form of motor contagion is entirely spontaneous and happens even if the task does not require it.

This paper is supported by the European Commission within the Horizon 2020 research and innovation program, under grant agreement No 870142, project APRIL (multipurpose robotics for mAniPulation of defoRmable materIaLs in manufacturing processes). N. F. Duarte is supported by FCT-IST fellowship grant PD/BD/135116/2017 and LARSyS-FCT project UIDB/50009/2020.

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Notes

  1. 1.

    Official repository of the Kinova Gen3 ROS package: https://github.com/Kinovarobotics/ros_kortex.

  2. 2.

    Official website of the gripper: https://robotiq.com/products/2f85-140-adaptive-robot-gripper.

  3. 3.

    Sample video of the human-robot interaction: https://www.youtube.com/watch?v=HVahS-0tn6g.

  4. 4.

    Optitrack website: https://optitrack.com/cameras/flex-13/.

  5. 5.

    Jamovi software website: https://www.jamovi.org.

  6. 6.

    General analyses for linear models Jamovi module: https://gamlj.github.io/.

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Author information

Authors and Affiliations

  1. Robotics, Brain and Cognitive Science Department (RBCS), Italian Institute of Technology, Genoa, Italy

    Linda Lastrico & Francesco Rea

  2. Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS), University of Genoa, Genoa, Italy

    Linda Lastrico, Alessandro Carfí & Fulvio Mastrogiovanni

  3. Institute for Systems and Robotics (ISR), Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal

    Nuno Ferreira Duarte & José Santos-Victor

  4. Cognitive Architecture for Collaborative Technologies Unit (CONTACT), Italian Institute of Technology, Genoa, Italy

    Alessandra Sciutti

Authors
  1. Linda Lastrico
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  2. Nuno Ferreira Duarte
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  3. Alessandro Carfí
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  4. Francesco Rea
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  5. Fulvio Mastrogiovanni
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  6. Alessandra Sciutti
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  7. José Santos-Victor
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Corresponding author

Correspondence to Linda Lastrico .

Editor information

Editors and Affiliations

  1. University of Florence, Florence, Italy

    Filippo Cavallo

  2. Qatar University, Doha, Qatar

    John-John Cabibihan

  3. University of Florence, Florence, Italy

    Laura Fiorini

  4. University of Florence, Florence, Italy

    Alessandra Sorrentino

  5. Wichita State University, Wichita, KS, USA

    Hongsheng He

  6. Qingdao University, Qingdao, China

    Xiaorui Liu

  7. National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan

    Yoshio Matsumoto

  8. National University of Singapore, Singapore, Singapore

    Shuzhi Sam Ge

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Lastrico, L. et al. (2022). If You Are Careful, So Am I! How Robot Communicative Motions Can Influence Human Approach in a Joint Task. In: Cavallo, F., et al. Social Robotics. ICSR 2022. Lecture Notes in Computer Science(), vol 13817. Springer, Cham. https://doi.org/10.1007/978-3-031-24667-8_24

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  • DOI: https://doi.org/10.1007/978-3-031-24667-8_24

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  • Online ISBN: 978-3-031-24667-8

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