Abstract
In social interactions, human movement is a rich source of information for all those who take part in the collaboration. In fact, a variety of intuitive messages are communicated through motion and continuously inform the partners about the future unfolding of the actions. A similar exchange of implicit information could support movement coordination in the context of Human-Robot Interaction. In this work, we investigate how implicit signaling in an interaction with a humanoid robot can lead to emergent coordination in the form of automatic speed adaptation. In particular, we assess whether different cultures – specifically Japanese and Italian – have a different impact on motor resonance and synchronization in HRI. Japanese people show a higher general acceptance toward robots when compared with Western cultures. Since acceptance, or better affiliation, is tightly connected to imitation and mimicry, we hypothesize a higher degree of speed imitation for Japanese participants when compared to Italians. In the experimental studies undertaken both in Japan and Italy, we observe that cultural differences do not impact on the natural predisposition of subjects to adapt to the robot.
References
[1] SoftBank Robotics, NAO [Online], Available: https://www.ald.softbankrobotics.com/enSearch in Google Scholar
[2] SoftBank Robotics, Pepper [Online], Available: https://www.ald.softbankrobotics.com/enSearch in Google Scholar
[3] D. Mondou, A. Prigent, A. Revel, A dynamic scenario by remote supervision: a serious game in the museum with a Nao robot, In: Advances in Computer Entertainment Technology (ACE2017), London, UK, 2017, 103–11610.1007/978-3-319-76270-8_8Search in Google Scholar
[4] M. Niemelä, A. Arvola, I. Aaltonen, Monitoring the acceptance of a social service robot in a shopping mall: first results, In: Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’17), 2017, 225–22610.1145/3029798.3038333Search in Google Scholar
[5] A. Sciutti, M. Mara, V. Tagliasco, G. Sandini, Humanizing human-robot interaction: On the importance of mutual understanding, IEEE Technology and Society Magazine, 2018, 37(1), 22–2910.1109/MTS.2018.2795095Search in Google Scholar
[6] R. Blake, M. Shiffrar, Perception of human motion, Annual Review of Psychology, 2007, 58, 47–7310.1146/annurev.psych.57.102904.190152Search in Google Scholar PubMed
[7] G. Sandini, A. Sciutti, F. Rea, Movement-based communication for humanoid-human interaction, In: A. Goswami, P. Vadakkepat (Eds.), Humanoid Robotics: A Reference, Springer, Dordrecht, 2018, 2169–219710.1007/978-94-007-6046-2_138Search in Google Scholar
[8] A. Bisio et al., Motor contagion during human-human and human-robot interaction, PLoS One, 2014, 9(8)10.1371/journal.pone.0106172Search in Google Scholar PubMed PubMed Central
[9] H. Lehmann, Y. Nagai, G. Metta, The Question of Cultural Sensitive Gesture Libraries in HRI - An Italian - Japanese Comparison, In: Proceedings of the ICDL-EpiRob 2016 – Workshop on Vision and the Development of Social Cognition, 2016Search in Google Scholar
[10] S. Martinez-Conde, S. L. Macknik, D. H. Hubel, The role of fixational eye movements in visual perception, Nature Reviews Neuroscience, 2004, 5, 229–24010.1038/nrn1348Search in Google Scholar PubMed
[11] H. Lehmann, I. Keller, R. Ahmadzadeh, F. Broz, Naturalistic Conversational Gaze Control for Humanoid Robots – A First Step, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 201710.1007/978-3-319-70022-9_52Search in Google Scholar
[12] M. Argyle, J. Dean, Eye-Contact, Distance and aflliation, Sociometry, 1965, 28(3), 289–30410.2307/2786027Search in Google Scholar
[13] A. Bisio, N. Stucchi, M. Jacono, L. Fadiga, T. Pozzo, Automatic versus voluntary motor imitation: Effect of visual context and stimulus velocity, PLoS One, 2010, 5(10), e1350610.1371/journal.pone.0013506Search in Google Scholar PubMed PubMed Central
[14] C. Bartneck, T. Nomura, T. Kanda, T. Suzuki, K. Kato, Cultural differences in attitudes towards robots, In: Proceedings of the AISB Symposium on Robot Companions, Hard Problems and Open Challenges in Human-Robot Interaction, Hatfield, 2005, 1–4Search in Google Scholar
[15] D. Li, P. P. Rau, Y. Li, A cross-cultural study: Effect of robot appearance and task, International Journal of Social Robotics, 2010, 2(2), 175–18610.1007/s12369-010-0056-9Search in Google Scholar
[16] S. Šabanović, C. C. Bennett, H. R. Lee, Towards culturally robust robots: A critical social perspective on robotics and culture, In: Proceedings of HRI Workshop on Culture-Aware Robotics, Bielefeld, 2014Search in Google Scholar
[17] F. Kaplan, Who is afraid of the humanoid? Investigating cultural differences in the acceptance of robots, International Journal of Humanoid Robotics, 2004, 1(03), 465–48010.1142/S0219843604000289Search in Google Scholar
[18] G. Knoblich, S. Butterfill, N. Sebanz, Psychological research on joint action: theory and data, Psychology of Learning and Motivation, Academic Press, 2011, 54, 59–10110.1016/B978-0-12-385527-5.00003-6Search in Google Scholar
[19] G. Rizzolatti, L. Craighero, The mirror-neuron system, Annual Review of Neuroscience, 2004, 27(1), 169–19210.1146/annurev.neuro.27.070203.144230Search in Google Scholar
[20] L. Craighero, G. Metta, G. Sandini, L. Fadiga, The mirror-neurons system: data and models, Progress in Brain Research, 2007, 164, 39–5910.1016/S0079-6123(07)64003-5Search in Google Scholar
[21] Y. Kanakogi, S. Itakura, Developmental correspondence between action prediction and motor ability in early infancy, Nature Communications, 2011, 2, 34110.1038/ncomms1342Search in Google Scholar PubMed
[22] T. Falck-Ytter, G. Gredebäck, C. von Hofsten, Infants predict other people’s action goals, Nature Neuroscience, 2006, 9(7), 878–87910.1038/nn1729Search in Google Scholar PubMed
[23] M. Bove, A. Tacchino, E. Pelosin, C. Moisello, G. Abbruzzese, M. F. Ghilardi, Spontaneous movement tempo is influenced by observation of rhythmical actions, Brain Research Bulletin, 2009, 80(3), 122–12710.1016/j.brainresbull.2009.04.008Search in Google Scholar PubMed
[24] L. Noy, E. Dekel, U. Alon, The mirror game as a paradigm for studying the dynamics of two people improvising motion together, In: Proceedings of the National Academy of Sciences, 2011, 108(52), 20947–2095210.1073/pnas.1108155108Search in Google Scholar PubMed PubMed Central
[25] A. Sciutti, A. Bisio, F. Nori, G. Metta, L. Fadiga, T. Pozzo, G. Sandini, Measuring human-robot interaction through motor resonance, International Journal of Social Robotics, 2012, 4(3), 223–23410.1007/s12369-012-0143-1Search in Google Scholar
[26] S. Kashi, S. Levy-Tzedek, Smooth leader or sharp follower? Playing the mirror game with a robot, Restorative Neurology and Neuroscience, 2018, 36(2), 147–15910.3233/RNN-170756Search in Google Scholar PubMed PubMed Central
[27] A. Sciutti, G. Sandini, Interacting with robots to investigate the bases of social interaction,IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2017, 25(12), 2295–230410.1109/TNSRE.2017.2753879Search in Google Scholar PubMed
[28] L. Amoruso, C. Urgesi, Contextual modulation of motor resonance during the observation of everyday actions, Neuroimage, 2016, 134, 74–8410.1016/j.neuroimage.2016.03.060Search in Google Scholar PubMed
[29] L. Amoruso, A. Finisguerra, C. Urgesi, Tracking the time course of top-down contextual effects on motor responses during action comprehension, Journal of Neuroscience, 2016, 36(46), 11590–1160010.1523/JNEUROSCI.4340-15.2016Search in Google Scholar PubMed PubMed Central
[30] B. Rauchbauer, J. Majdandžić, A. Hummer, C. Windischberger, C. Lamm, Distinct neural processes are engaged in the modulation of mimicry by social group-membership and emotional expressions, Cortex, 2015, 70, 49–6710.1016/j.cortex.2015.03.007Search in Google Scholar PubMed
[31] P. Molenberghs, V. Halász, J. B. Mattingley, E. J. Vanman, R. Cunnington, Seeing is believing: Neural mechanisms of action-perception are biased by team membership, Human Brain Mapping, 2013, 34(9), 2055–206810.1002/hbm.22044Search in Google Scholar PubMed PubMed Central
[32] T. L. Chartrand, J. L. Lakin, The antecedents and consequences of human behavioral mimicry, Annual Review of Psychology, 2013, 64, 285–30810.1146/annurev-psych-113011-143754Search in Google Scholar PubMed
[33] M. Baldassarre, S. Feller, Cultural variations in personal space: theory, methods, and evidence, Ethos, 1975, 3(4), 481–50310.1525/eth.1975.3.4.02a00020Search in Google Scholar
[34] G. Metta, L. Natale, F. Nori, G. Sandini, The iCub project: An open source platform for research in embodied cognition, In: Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO, 2011, 24–2610.1109/ARSO.2011.6301975Search in Google Scholar
[35] P. Viviani, T. Flash, Minimum-jerk, two-thirds power law, and isochrony: converging approaches to movement planning, Journal of Experimental Psychology: Human Perception and Performance, 1995, 21(1), 32–5310.1037/0096-1523.21.1.32Search in Google Scholar
[36] G. Catavitello, Y. P. Ivanenko, F. Lacquaniti, P. Viviani, Drawing ellipses in water: evidence for dynamic constraints in the relation between velocity and path curvature, Experimental Brain Research, 2016, 234(6), 1649–165710.1007/s00221-016-4569-9Search in Google Scholar PubMed
[37] N. Noceti, F. Rea, A. Sciutti, F. Odone, G. Sandini, View-invariant robot adaptation to human action timing, In: Proceedings of SAI Intelligent Systems Conference, Springer, Cham, 2018, 804–82110.1007/978-3-030-01054-6_56Search in Google Scholar
[38] U. Pattacini, F. Nori, L. Natale, G. Metta, G. Sandini, An experimental evaluation of a novel minimum-jerk Cartesian controller for humanoid robots, In: Proceedings of IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS, 2010, 1668–167410.1109/IROS.2010.5650851Search in Google Scholar
[39] T. Chaminade, D. W. Franklin, E. Oztop, G. Cheng, Motor interference between humans and humanoid robots: Effect of biological and artificial motion, In: Proceedings of 2005 4th IEEE International Conference on Development and Learning, 2005, 96101Search in Google Scholar
[40] G. Metta, P. Fitzpatrick, L. Natale, YARP – Yet Another Robot Platform, version 2.3.20, International Journal of Advanced Robotic Systems, 2006, 3(1), 810.5772/5761Search in Google Scholar
[41] ICubForwardKinematics, 2014, http://wiki.icub.org/wiki/ICubForwardKinematicsSearch in Google Scholar
[42] D. Eizicovits, Y. Edan, I. Tabak, S. Levy-Tzedek, Robotic gaming prototype for upper limb exercise: Effects of age and embodiment on user preferences and movement, Restorative Neurology and Neuroscience, 2018, 36(2), 261–27410.3233/RNN-170802Search in Google Scholar PubMed PubMed Central
[43] A. Cherubini, R. Passama, A. Meline, A. Crosnier, P. Fraisse, Multimodal control for human-robot cooperation, In: Proceedings of IEEE International Conference on Intelligent Robots and Systems, 2013, 2202–220710.1109/IROS.2013.6696664Search in Google Scholar
[44] B. Nemec, N. Likar, A. Gams, A. Ude, Bimanual human robot cooperation with adaptive stiffness control, In: Proceedings of IEEE-RAS International Conference on Humanoid Robots, 2016, 607–61310.1109/HUMANOIDS.2016.7803337Search in Google Scholar
© 2019 Fabio Vannucci et al., published by De Gruyter
This work is licensed under the Creative Commons Attribution 4.0 Public License.