Remote HRI: a Methodology for Maintaining COVID-19 Physical Distancing and Human Interaction Requirements in HRI Studies
Tóm tắt
Observing how humans and robots interact is an integral part of understanding how they can effectively coexist. This ability to undertake these observations was taken for granted before the COVID-19 pandemic restricted the possibilities of performing HRI study-based interactions. We explore the problem of how HRI research can occur in a setting where physical separation is the most reliable way of preventing disease transmission. We present the results of an exploratory experiment that suggests Remote-HRI (R-HRI) studies may be a viable alternative to traditional face-to-face HRI studies. An R-HRI study minimizes or eliminates in-person interaction between the experimenter and the participant and implements a new protocol for interacting with the robot to minimize physical contact. Our results showed that participants interacting with the robot remotely experienced a higher cognitive workload, which may be due to minor cultural and technical factors. Importantly, however, we also found that whether participants interacted with the robot in-person (but socially distanced) or remotely over a network, their experience, perception of, and attitude towards the robot were unaffected.
Tài liệu tham khảo
Al-Taee, M. A., Kapoor, R., Garrett, C., & Choudhary, P. (2016). Acceptability of robot assistant in management of Type 1 diabetes in children. Diabetes Technology & Therapeutics, 18(9), 551–554.
Andreasen, M.S., Nielsen, H.V., Schrøder, S.O., & Stage, J. (2007). What Happened to Remote Usability Testing? An Empirical Study of Three Methods. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 1405–14. CHI ‘07. San Jose, California, USA: Association for Computing Machinery. https://doi.org/10.1145/1240624.1240838.
Barata, A.N. (2019) Social Robots as a Complementary Therapy in Chronic, Progressive Diseases. In Robotics in Healthcare, 95–102. Springer.
Bruun, A., Gull, P., Hofmeister, L., & Stage, J. (2009). Let your users do the testing: A comparison of three remote asynchronous usability testing methods. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 1619–28. CHI ‘09. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/1518701.1518948.
Burke, J., & Murphy, R. (2007). RSVP: An investigation of remote shared visual presence as common ground for human-robot teams. In Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction, 161–68. HRI ‘07. Arlington, Virginia, USA: Association for Computing Machinery. https://doi.org/10.1145/1228716.1228738.
Byrne, S. (n.d.) Zenbo family robot destroys Computex with cuteness before it even begins. CNET. Accessed 26 July 2020. https://www.cnet.com/news/zenbo-family-robot-destroys-computex-with-cuteness-before-it-even-begins/
Cabecinhas, A.R.G., Roloff, T., Stange, M., Bertelli, C., Huber, M., Ramette, A., Chen, C. et al (2021) SARS-CoV-2 N501Y introductions and transmissions in Switzerland from beginning of October 2020 to February 2021 – Implementation of Swiss-wide diagnostic screening and whole genome sequencing. MedRxiv, January, 2021.02.11.21251589. https://doi.org/10.1101/2021.02.11.21251589.
Carpinella, C.M., Wyman, A.B., Perez, M.A., Stroessner, S.J. (2017). The robotic social attributes scale (RoSAS) development and validation. In Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, 254–262.
Castillo, J.C., Rex Hartson, H., & Hix, D. (1998). Remote usability evaluation: Can users report their own critical incidents? In CHI 98 conference summary on human factors in Computing systems - CHI ‘98, 253–254. : ACM Press. https://doi.org/10.1145/286498.286736.
CDC. (2020). Coronavirus disease 2019 (COVID-19). Centers for Disease Control and Prevention. 11 February 2020. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-with-medical-conditions.html
Chalil Madathil, K., & Greenstein, J. S. (2017). An investigation of the efficacy of collaborative virtual reality systems for moderated remote usability testing. Applied Ergonomics, 65(November), 501–514. https://doi.org/10.1016/j.apergo.2017.02.011.
Chien, S.-E., Chu, L., Lee, H.-H., Yang, C.-C., Lin, F.-H., Yang, P.-L., Wang, T.-M., & Yeh, S.-L. (2019). Age difference in perceived ease of use, curiosity, and implicit negative attitude toward robots. ACM Transactions on Human-Robot Interaction, 8(2), 9:1–9:19. https://doi.org/10.1145/3311788.
Chiou, M., Bieksaite, G., Hawes, N., Stolkin, R. (2016). Human-initiative variable autonomy: An experimental analysis of the interactions between a human operator and a remotely operated Mobile robot which also possesses autonomous capabilities. In AAAI Fall Symposia.
Chivarov, N., Chikurtev, D., Chivarov, S., Pleva, M., Ondas, S., Juhar, J., & Yovchev, K. (2019). Case study on human-robot interaction of the remote-controlled service robot for elderly and disabled care. Computing and Informatics, 38(5), 1210–1236.
De Winter, J. C. F. (2013). Using the Student’s t-test with extremely small sample sizes. Practical Assessment, Research, and Evaluation, 18(1), 10. https://doi.org/10.7275/e4r6-dj05.
Dörndorfer, J., & Seel, C. (2020). Context modeling for the adaption of Mobile business processes – An empirical usability evaluation. Information Systems Frontiers. https://doi.org/10.1007/s10796-020-10073-w.
Fang, X., & Holsapple, C. W. (2011). Impacts of navigation structure, task complexity, and users’ domain knowledge on web site usability—An empirical study. Information Systems Frontiers, 13(4), 453–469. https://doi.org/10.1007/s10796-010-9227-3.
Feil-Seifer, D., Haring, K. S., Rossi, S., Wagner, A. R., & Williams, T. (2020). Where to next? The impact of COVID-19 on human-robot interaction research. ACM Transactions on Human-Robot Interaction, 10(1), 1–7. https://doi.org/10.1145/3405450.
Ghasemi, A., & Zahediasl, S. (2012). Normality tests for statistical analysis: A guide for non-statisticians. International Journal of Endocrinology and Metabolism, 10(2), 486–489. https://doi.org/10.5812/ijem.3505.
Hammontree, M., Weiler, P., & Nayak, N. (1994). Remote usability testing. Interactions, 1(3), 21–25.
Hart, S.G. (2006). NASA-task load index (NASA-TLX); 20 years later. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 50:904–8. Sage Publications Sage CA.
Hartson, H. R., Castillo, J.C., Kelso, J., Neale, W.C. (1996). Remote evaluation: The network as an extension of the usability laboratory. In Proceedings of the SIGCHI conference on human factors in Computing systems common ground - CHI ‘96, 228–235. Vancouver, British Columbia, Canada: ACM Press. https://doi.org/10.1145/238386.238511.
Henkemans, B., Olivier, A., Van der Pal, S. Werner, I, Neerincx, M.A., & Looije, R. (2017). Learning with Charlie: A robot buddy for children with diabetes. In Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, 406–406.
Hertzum, M., Borlund, P., & Kristoffersen, K. B. (2015). What do thinking-aloud participants say? A comparison of moderated and unmoderated usability sessions. International Journal of Human–Computer Interaction, 31(9), 557–570. https://doi.org/10.1080/10447318.2015.1065691.
Honig, S., & Oron-Gilad, T (2020). Comparing laboratory user studies and video-enhanced web surveys for eliciting user gestures in human-robot interactions. In Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, 248–50. HRI ‘20. Cambridge, United Kingdom: Association for Computing Machinery. https://doi.org/10.1145/3371382.3378325.
Huber, A., Weiss, A. (2017). Developing human-robot interaction for an industry 4.0 robot: How industry workers helped to improve remote-HRI to physical-HRI. In Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, 137–38. HRI ‘17. Vienna, Austria: Association for Computing Machinery. https://doi.org/10.1145/3029798.3038346.
International Labour Organization. (2021). ILO Monitor: COVID-19 and the World of Work. 7th Edition. Briefing note. 25 January 2021. http://www.ilo.org/global/topics/coronavirus/impacts-and-responses/WCMS_767028/lang%2D%2Den/index.htm.
Jitsi.Org (2021). Jitsi. 2021. https://jitsi.org/.
Killerby, M.E., Link-Gelles, R., Haight, S.C., Schrodt, C.A., England, L. (2020). Characteristics Associated with Hospitalization Among Patients with COVID-19 — Metropolitan Atlanta, Georgia, March–April 2020. MMWR. Morbidity and Mortality Weekly Report 69 (June). https://doi.org/10.15585/mmwr.mm6925e1.
Kim, H., Kim, J., & Lee, Y. (2005). An empirical study of use contexts in the Mobile internet, focusing on the usability of information architecture. Information Systems Frontiers, 7(2), 175–186. https://doi.org/10.1007/s10796-005-1486-z.
Laugwitz, B., Held, T., Schrepp, M. (2008). Construction and evaluation of a user experience questionnaire. In HCI and Usability for Education and Work, edited by Andreas Holzinger, 63–76. Lecture notes in computer science. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-540-89350-9_6.
Lee, K., Lee, K. Y., & Sheehan, L. (2020). Hey Alexa! A magic spell of social glue?: Sharing a smart voice assistant speaker and its impact on users’ perception of group harmony. Information Systems Frontiers, 22(3), 563–583. https://doi.org/10.1007/s10796-019-09975-1.
Macefield, R. (2009). How to specify the participant group size for usability studies: A practitioner’s guide. Journal of Usability Studies, 5(1), 34–45.
Mackey, B.A., Bremner, P.A., Giuliani, M. (2020). The Effect of Virtual Reality Control of a Robotic Surrogate on Presence and Social Presence in Comparison to Telecommunications Software. In Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, 349–51. HRI ‘20. Cambridge, United Kingdom: Association for Computing Machinery. https://doi.org/10.1145/3371382.3378268.
Martinez-Martin, E., & del Pobil, A.P. (2018). Personal robot assistants for elderly care: An overview. In Personal Assistants: Emerging Computational Technologies, 77–91. Springer.
Mumm, J., & Mutlu, B. (2011). Human-robot proxemics: Physical and psychological distancing in human-robot interaction. In Proceedings of the 6th International Conference on Human-Robot Interaction, 331–338.
Nagy, G.M., Young, J.E., Anderson, J.E. (2015). Are tangibles really better? Keyboard and joystick outperform TUIs for remote robotic locomotion control. In Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction Extended Abstracts, 41–42. HRI’15 extended abstracts. Portland, Oregon, USA: Association for Computing Machinery. https://doi.org/10.1145/2701973.2701978.
Nomura, T., Suzuki, T., Kanda, T., & Kato, K. (2006). Altered attitudes of people toward robots: Investigation through the negative attitudes toward robots scale. In Proc. AAAI-06 Workshop on Human Implications of Human-Robot Interaction, 2006:29–35.
Oh, S., & Oh, Y.H.. (2019). Understanding the preference of the elderly for companion robot design. In International Conference on Applied Human Factors and Ergonomics, 92–103. Springer.
Papadopoulos, F., Dautenhahn, K., & Ho, W.C. (2013). Behavioral analysis of human-human remote social interaction mediated by an interactive robot in a cooperative game scenario. In Handbook of Research on Technoself: Identity in a Technological Society, 637–65. IGI Global.
Prasov, Z. (2012). Shared gaze in remote spoken HRI during distributed military operation. In Proceedings of the Seventh Annual ACM/IEEE International Conference on Human-Robot Interaction, 211–12. HRI ‘12. Boston, Massachusetts, USA: Association for Computing Machinery. https://doi.org/10.1145/2157689.2157760.
Price-Haywood, E. G., Burton, J., Fort, D., & Seoane, L. (2020). Hospitalization and mortality among black patients and white patients with Covid-19. New England Journal of Medicine, 382, 2534–2543. https://doi.org/10.1056/NEJMsa2011686.
Qian, K., Niu, J., & Yang, H. (2013). Developing a gesture based remote human-robot interaction system using Kinect. International Journal of Smart Home, 7(4), 203–208.
Robinson, H., MacDonald, B., Kerse, N., & Broadbent, E. (2013). The psychosocial effects of a companion robot: A randomized controlled trial. Journal of the American Medical Directors Association, 14(9), 661–667.
Rubin, J., & Chisnell, D. (2008). Handbook of usability testing: How to plan. John Wiley & Sons.
Schneider, S., & Kummert, F. (2018). Comparing the effects of social robots and virtual agents on exercising motivation. In International Conference on Social Robotics, 451–61. Springer.
Sierra, S.D., Jiménez, M.F., Múnera, M.C., Frizera-Neto, A., Cifuentes, C.A.. (2019). Remote-operated multimodal Interface for therapists during Walker-assisted gait rehabilitation: A preliminary assessment. In Proceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction, 528–29. HRI ‘19. Daegu, Republic of Korea: IEEE press.
Stokes, E.K., Zambrano, L.D., Anderson, K.N., Marder, E.P., Raz, K.M., Felix, S.El B., Tie, Y, & Fullerton, K.E. (2020). Coronavirus disease 2019 case surveillance — United States, January 22–May 30, 2020. MMWR. Morbidity and Mortality Weekly Report 69 (June). https://doi.org/10.15585/mmwr.mm6924e2.
Stubbs, K., Wettergreen, D., Nourbakhsh, I. (2008). Using a robot proxy to create common ground in exploration tasks. In Proceedings of the 3rd ACM/IEEE International Conference on Human Robot Interaction, 375–82. HRI ‘08. Amsterdam, the Netherlands: Association for Computing Machinery. https://doi.org/10.1145/1349822.1349871.
Thompson, K.E., Rozanski, E.P., & Haake, A.R.. (2004).Here, there, anywhere: Remote usability testing that works. In Proceedings of the 5th conference on information technology education, 132–137.
UNESCO. (2021). UNESCO figures show two thirds of an academic year lost on average worldwide due to Covid-19 school closures. UNESCO. 25 January 2021. https://en.unesco.org/news/unesco-figures-show-two-thirds-academic-year-lost-average-worldwide-due-covid-19-school
United Nations. (2020). UN secretary-General’s policy brief: The impact of COVID-19 on women | digital library: Publications. UN Women. 4 September 2020. https://www.unwomen.org/en/digital-library/publications/2020/04/policy-brief-the-impact-of-covid-19-on-women.
Vasalou, A., Ng, B.D., Wiemer-Hastings, P., & Oshlyansky, L. (2004). Human-Moderated Remote User Testing: Protocols and Applications. In 8th ERCIM Workshop, User Interfaces for All, Wien, Austria. Vol. 19. sn.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926.
Walters, Michael L., Kerstin Dautenhahn, René Te Boekhorst, Kheng Lee Koay, Dag Sverre Syrdal, and Chrystopher L. Nehaniv. (2009). An empirical framework for human-robot proxemics. Procs of New Frontiers in Human-Robot Interaction.
Wang, Zijun, Fabian Schmidt, Yiska Weisblum, Frauke Muecksch, Christopher O. Barnes, Shlomo Finkin, Dennis Schaefer-Babajew, et al. 2021. ‘MRNA vaccine-elicited antibodies to SARS-CoV-2 and circulating variants’. BioRxiv, January, 2021.01.15.426911. https://doi.org/10.1101/2021.01.15.426911.
World Health Organization and others. (2020). Transmission of SARS-CoV-2: Implications for infection prevention precautions: Scientific brief, 09 July 2020. World Health Organization.
Xue, C., Qiao, Y., Murray, N. (2020). Enabling human-robot-interaction for remote robotic operation via augmented reality. In 2020 IEEE 21st International Symposium on ‘A World of Wireless, Mobile and Multimedia Networks’ (WoWMoM), 194–96. https://doi.org/10.1109/WoWMoM49955.2020.00046.
Yanco, H.A., Baker, M., Casey, R., Chanler, A., Desai, M., Hestand, D., Keyes, B., & Thoren, P. (2005). ‘Improving human-robot interaction for remote robot operation’. In AAAI, 5:1743–1744.
Zenbo | Intelligent Robot. (n.d.) ASUS Global. . https://www.asus.com/Commercial-Intelligent-Robot/Zenbo/
Zhao, Z., & McEwen, R. (2021). ‘Luka Luka - investigating the interaction of children and their home Reading companion robot: A longitudinal remote study’. In Companion of the 2021 ACM/IEEE International Conference on Human-Robot Interaction, 141–43. HRI ‘21 companion. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3434074.3447146.
