Analyzing Human Perceptions of a MEDEVAC Robot in a Simulated Evacuation Scenario
Abstract: The use of autonomous systems in medical evacuation (MEDEVAC) scenarios is promising, but existing implementations overlook key insights from human-robot interaction (HRI) research. Studies on human-machine teams demonstrate that human perceptions of a machine teammate are critical in governing the machine's performance. Here, we present a mixed factorial design to assess human perceptions of a MEDEVAC robot in a simulated evacuation scenario. Participants were assigned to the role of casualty (CAS) or bystander (BYS) and subjected to three within-subjects conditions based on the MEDEVAC robot's operating mode: autonomous-slow (AS), autonomous-fast (AF), and teleoperation (TO). During each trial, a MEDEVAC robot navigated an 11-meter path, acquiring a casualty and transporting them to an ambulance exchange point while avoiding an idle bystander. Following each trial, subjects completed a questionnaire measuring their emotional states, perceived safety, and social compatibility with the robot. Results indicate a consistent main effect of operating mode on reported emotional states and perceived safety. Pairwise analyses suggest that the employment of the AF operating mode negatively impacted perceptions along these dimensions. There were no persistent differences between casualty and bystander responses.
- C. D. Newgard, R. H. Schmicker, J. R. Hedges, J. P. Trickett, D. P. Davis, E. M. Bulger, T. P. Aufderheide, J. P. Minei, J. S. Hata, K. D. Gubler, T. B. Brown, J.-D. Yelle, B. Bardarson, and G. Nichol, “Emergency medical services intervals and survival in trauma: Assessment of the “golden hour” in a north american prospective cohort,” Annals of Emergency Medicine, vol. 55, no. 3, pp. 235–246.e4, 2010.
- G. A. Wilde and R. R. Murphy, “User interface for unmanned surface vehicles used to rescue drowning victims,” in 2018 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR). IEEE, 2018, pp. 1–8.
- P. Jeler, Eduard G., “The use of autonomous systems for evacuation and medical support,” International Scientific Conference ”Strategies XXI”, no. 1, pp. 371–378, 2019, copyright - Copyright ”Carol I” National Defence University 2019; Last updated - 2020-04-02.
- V. Groom and C. Nass, “Can robots be teammates?: Benchmarks in human–robot teams,” Interaction Studies, vol. 8, no. 3, pp. 483–500, 2007.
- C. Bartneck, D. Kulić, E. Croft, and S. Zoghbi, “Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots,” International Journal of Social Robotics, vol. 1, no. 1, pp. 71–81, Jan 2009.
- C. M. Carpinella, A. B. Wyman, M. A. Perez, and S. J. Stroessner, “The robotic social attributes scale (rosas): Development and validation,” in Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, ser. HRI ’17. New York, NY, USA: Association for Computing Machinery, 2017, p. 254–262.
- C. M. Humphrey and J. A. Adams, “Human roles for robot augmented first response,” in 2015 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR). IEEE, 2015, pp. 1–6.
- R. Murphy, “Human-robot interaction in rescue robotics,” IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 34, no. 2, pp. 138–153, 2004.
- D. Kulić and E. A. Croft, “Estimating robot induced affective state using hidden markov models,” ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication, pp. 257–262, 2006.
- D. Kulic and E. Croft, “Affective state estimation for human–robot interaction,” Robotics, IEEE Transactions on, vol. 23, pp. 991 – 1000, 11 2007.
- K. A. Barchard, L. Lapping-Carr, R. S. Westfall, A. Fink-Armold, S. B. Banisetty, and D. Feil-Seifer, “Measuring the perceived social intelligence of robots,” vol. 9, no. 4, sep 2020.
- L. S. Lambert and D. A. Newman, “Construct development and validation in three practical steps: Recommendations for reviewers, editors, and authors,” Organizational Research Methods, vol. 26, no. 4, pp. 574–607, 2023.
- R. Grant, A. Goodie, and P. Doshi, “The human-machine teammate inventory (hmti): Scale development and validation,” Feb 2024.
- A. C. Costa, A. Fulmer, and N. Anderson, “Trust in work teams: An integrative review, multilevel framework, and future directions,” Journal of Organizational Behavior, vol. 39, 06 2017.
- M. K. M. Rabby, M. Khan, A. Karimoddini, and S. Jiang, “Modeling of trust within a human-robot collaboration framework,” 12 2020.
- J. Delmerico, S. Mintchev, A. Giusti, B. Gromov, K. Melo, T. Horvat, C. Cadena, M. Hutter, A. Ijspeert, D. Floreano, L. M. Gambardella, R. Siegwart, and D. Scaramuzza, “The current state and future outlook of rescue robotics,” Journal of Field Robotics, vol. 36, no. 7, pp. 1171–1191, 2019.
- F. E. Schneider, D. Wildermuth, and H.-L. Wolf, “Elrob and eurathlon: Improving search & rescue robotics through real-world robot competitions,” in 2015 10th International Workshop on Robot Motion and Control (RoMoCo), 2015, pp. 118–123.
- R. Edlinger, C. Föls, and A. Nüchter, “An innovative pick-up and transport robot system for casualty evacuation,” in 2022 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 2022, pp. 67–73.
- J. L. Casper and M. J. Micire, “The aaai-2002 robot rescue,” AI Magazine, vol. 24, no. 1, pp. 51–59, 2003.
- T. Takahashi and S. Tadokoro, “Working with robots in disasters,” IEEE Robotics and Automation Magazine, vol. 9, no. 3, pp. 34–39, Sep. 2002.
- R. R. Murphy and S. Stover, “Rescue robots for mudslides: A descriptive study of the 2005 la conchita mudslide response,” Journal of Field Robotics, vol. 25, no. 1-2, pp. 3–16, 2008.
- J. Drury, J. Scholtz, and H. Yanco, “Awareness in human-robot interactions,” vol. 1, 11 2003, pp. 912 – 918 vol.1.
- R. P. Saputra and P. Kormushev, “Resqbot: A mobile rescue robot with immersive teleperception for casualty extraction,” in Towards Autonomous Robotic Systems, M. Giuliani, T. Assaf, and M. E. Giannaccini, Eds. Cham: Springer International Publishing, 2018, pp. 209–220.
- B. Ruppert, “Robots to rescue wounded on battlefield,” U.S. Army, November 2010.
- B. Choi, W. Lee, G. Park, Y. Lee, J. Min, and S. Hong, “Development and control of a military rescue robot for casualty extraction task,” Journal of Field Robotics, vol. 36, no. 4, pp. 656–676, 2019.
- R. P. Saputra, N. Rakicevic, I. Kuder, J. Bilsdorfer, A. Gough, A. Dakin, E. de Cocker, S. Rock, R. Harpin, and P. Kormushev, “Resqbot 2.0: An improved design of a mobile rescue robot with an inflatable neck securing device for safe casualty extraction,” Applied Sciences, vol. 11, no. 12, 2021.
- K. M. Tsui, M. Desai, and H. A. Yanco, “Considering the bystander’s perspective for indirect human-robot interaction,” in 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2010, pp. 129–130.
- T. Bailey, J. Nieto, and E. Nebot, “Consistency of the fastslam algorithm,” in Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006. IEEE, 2006, pp. 424–429.
- R. A. Fisher, “Statistical methods for research workers,” in Breakthroughs in statistics: Methodology and distribution. Springer, 1970, pp. 66–70.
- G. M. Sullivan and A. R. Artino, Jr, “Analyzing and interpreting data from likert-type scales,” J Grad Med Educ, vol. 5, no. 4, pp. 541–542, Dec. 2013.
- G. Norman, “Likert scales, levels of measurement and the “laws” of statistics,” Advances in health sciences education, vol. 15, pp. 625–632, 2010.
- G. Rickards, C. Magee, and A. R. Artino Jr, “You can’t fix by analysis what you’ve spoiled by design: developing survey instruments and collecting validity evidence,” Journal of graduate medical education, vol. 4, no. 4, pp. 407–410, 2012.
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