Abstract
Adaptive robots that collaborate with humans in shared task environments are expected to enhance production efficiency and flexibility in a near future. In this context, the question of acceptance of such a collaboration by human workers is essential for a successful implementation. Augmenting the robot-to-human communication channel with situation-specific and explanatory information might increase the workers’ willingness to collaborate with artificial counterparts, as a robot that provides guidance and explanation might be perceived as more cooperative in a social sense. However, the effects of using different augmentation strategies and parameters have not yet been sufficiently explored. This paper examines the usage of augmenting industrial robots involved in shared task environments by conducting an evaluation in a virtual reality (VR) setting. The results provide a first step towards an iterative design process aiming to facilitate and enhance the collaboration between human’s and robot’s in industrial contexts.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alsuraykh, N.H., Wilson, M.L., Tennent, P., Sharples, S.: How stress and mental workload are connected. In: Mayora, O., Forti, S., Meyer, J., Mamykina, L. (eds.) Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare, pp. 371–376. ACM, New York (2019). https://doi.org/10.1145/3329189.3329235
Arntz, A., Eimler, S.C.: Experiencing AI in VR: a qualitative study on designing a human-machine collaboration scenario. In: HCI INTERNATIONAL 2020–22nd International Conference on Human-Computer Interaction, Copenhagen, Denmark (2020)
Bailenson, J., Blascovich, J., Beall, A.: Interpersonal distance in immersive virtual environments. Pers. Soc. Psychol. Bull. 29, 819–833 (2003). https://doi.org/10.1177/014616720302900700210.1177/0146167203029007002
Bainbridge, W., Hart, J., Kim, E., Scassellati, B.: The effect of presence on human-robot interaction, pp. 701–706 (2008). https://doi.org/10.1109/ROMAN.2008.4600749
Banks, A., Millward, L.: Distributed mental models: mental models in distributed cognitive systems. J. Mind Behav. 30, 249–266 (2009)
Bauer, A., Wollherr, D., Buss, M.: Human-robot collaboration: a survey. Int. J. Humanoid Rob. 5, 47–66 (2008). https://doi.org/10.1142/S0219843608001303
Biocca, F.: The cyborg’s dilemma: progressive embodiment in virtual environments [1]. J. Comput.-Mediated Commun. 3(2) (1997). https://doi.org/10.1111/j.1083-6101.1997.tb00070.x
Bruemmer, D.J., Few, D.A., Boring, R.L., Marble, J.L., Walton, M.C., Nielsen, C.W.: Shared understanding for collaborative control. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 35(4), 494–504 (2005). https://doi.org/10.1109/TSMCA.2005.850599
Chan, S.F., La Greca, A.M.: Perceived stress scale (PSS). In: Gellman, M.D., Turner, J.R. (eds.) Encyclopedia of Behavioral Medicine, pp. 1454–1455. Springer, New York (2013). https://doi.org/10.1007/978-1-4419-1005-9_773
Cramton, C.D.: The mutual knowledge problem and its consequences for dispersed collaboration. Organ. Sci. 12(3), 346–371 (2001). https://doi.org/10.1287/orsc.12.3.346.10098
Daugherty, P.R., Wilson, H.J.: Human + Machine: Reimagining Work in the Age of AI. Harvard Business Review Press, La Vergne (2018). https://ebookcentral.proquest.com/lib/gbv/detail.action?docID=5180063
Ende, T., Haddadin, S., Parusel, S., Wüsthoff, T., Hassenzahl, M., Albu-Schäeffer, A.: A human-centered approach to robot gesture based communication within collaborative working processes, pp. 3367–3374, September 2011. https://doi.org/10.1109/IROS.2011.6094592
Grand, J.A., Braun, M.T., Kuljanin, G., Kozlowski, S.W.J., Chao, G.T.: The dynamics of team cognition: a process-oriented theory of knowledge emergence in teams. J. Appl. Psychol. 101(10), 1353–1385 (2016). https://doi.org/10.1037/apl0000136
Hart, S.G., Staveland, L.E.: Development of NASA-TLX (task load index): results of empirical and theoretical research. In: Human Mental Workload, Advances in Psychology, vol. 52, pp. 139–183. Elsevier (1988). https://doi.org/10.1016/S0166-4115(08)62386-9
Heerink, M., Krose, B., Evers, V., Wielinga, B.: Influence of social presence on acceptance of an assistive social robot and screen agent by elderly users. Adv. Robot. 23, 1909–1923 (2009). https://doi.org/10.1163/016918609X12518783330289
Hellström, T., Bensch, S.: Understandable robots. Paladyn J. Behav. Robot. 9, 110–123 (2018). https://doi.org/10.1515/pjbr-2018-0009
Hoffman, G., et al.: Robot presence and human honesty: experimental evidence, vol. 2015, March 2015. https://doi.org/10.1145/2696454.2696487
ISO: Iso 10218–1:2011 (2011). https://www.iso.org/standard/51330.html. Accessed 13 Mar 2020
Koay, K.L., et al.: Initial design, implementation and technical evaluation of a context-aware proxemics planner for a social robot. In: Kheddar, A., et al. (eds.) Social Robotics. Lecture Notes in Computer Science, vol. 10652, pp. 12–22. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-70022-9_2
Leser: Safety valve (2020). https://www.leser.com/de-de/produkte/api/type-526/. Accessed 28 Mar 2020
Matsas, E., Vosniakos, G.-C.: Design of a virtual reality training system for human–robot collaboration in manufacturing tasks. Int. J. Interact. Des. Manuf. (IJIDeM) 11(2), 139–153 (2015). https://doi.org/10.1007/s12008-015-0259-2
Müller-Abdelrazeq, S.L., Schönefeld, K., Haberstroh, M., Hees, F.: Interacting with collaborative robots—a study on attitudes and acceptance in industrial contexts. In: Korn, O. (ed.) Social Robots: Technological, Societal and Ethical Aspects of Human-Robot Interaction. HIS, pp. 101–117. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-17107-0_6
Mumm, J., Mutlu, B.: Human-robot proxemics. In: Billard, A., Kahn, P., Adams, J.A., Trafton, G. (eds.) Proceedings of the 6th international conference on Human-robot interaction - HRI 2011, p. 331. ACM Press, New York (2011). https://doi.org/10.1145/1957656.1957786
Müller, S.L., Schröder, S., Jeschke, S., Richert, A.: Design of a robotic workmate. In: Duffy, V.G. (ed.) DHM 2017. LNCS, vol. 10286, pp. 447–456. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-58463-8_37
Müller-Abdelrazeq, S.L., Stiehm, S., Haberstroh, M., Hees, F.: Perceived effects of cycle time in human-robot-interaction. In: 2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), pp. 25–30. IEEE (27092018–29092018). https://doi.org/10.1109/ARSO.2018.8625819
Nijholt, A.: Disappearing computers, social actors and embodied agents. In: Sourin, A., Soon, S.H., Kunii, T. (eds.) 2003 International Conference on Cyberworlds, pp. 128–134. IEEE Computer Society, Los Alamitos (2003). https://doi.org/10.1109/CYBER.2003.1253445
Nomura, T., Suzuki, T., Kanda, T., Kato, K.: Measurement of negative attitudes toward robots. Interact. Stud. 7(3), 437–454 (2006)
Oh, C.S., Bailenson, J.N., Welch, G.F.: A systematic review of social presence: definition, antecedents, and implications. Front. Robot. AI 5 (2018). https://doi.org/10.3389/frobt.2018.00114
Peltokorpi, V., Hood, A.C.: Communication in theory and research on transactive memory systems: a literature review. Top. Cogn. Sci. 11(4), 644–667 (2019). https://doi.org/10.1111/tops.12359
Philipsen, M., Rehm, M., Moeslund, T.: Industrial human-robot collaboration, pp. 35–38, July 2018. https://doi.org/10.21437/AI-MHRI.2018-9
Reeves, B., Nass, C.: The Media Equation: How People Treat Computers, Television, and New Media Like Real People and PLA. Bibliovault OAI Repository. The University of Chicago Press, Chicago (1996)
Schmidtler, J., Hoelzel, C., Knott, V., Bengler, K.: Human centered assistance applications for production. In: 5th International Conference on Applied Human Factors and Ergonomics, Krakow, Poland, July 2014. https://doi.org/10.13140/RG.2.1.1608.7203
Shah, J., Wiken, J., Williams, B., Breazeal, C.: Improved human-robot team performance using chaski, a human-inspired plan execution system. In: Billard, A., Kahn, P., Adams, J.A., Trafton, G. (eds.) Proceedings of the 6th International Conference on Human-Robot Interaction - HRI 2011, p. 29. ACM Press, New York (2011). https://doi.org/10.1145/1957656.1957668
Wegner, D.M., Erber, R., Raymond, P.: Transactive memory in close relationships. J. Pers. Soc. Psychol. 61, 923–929 (1991)
Witmer, B.G., Jerome, C.J., Singer, M.J.: The factor structure of the presence questionnaire. Presence Teleoperators Virtual Environ. 14(3), 298–312 (2005). https://doi.org/10.1162/105474605323384654
Acknowledgments
Many thanks go to Dustin Keßler, Dr. Carolin Straßmann, Nele Borgert, Dr. Laura Hoffmann and Sarah Zielinski for their advice, comments to the manuscript and encouragement while conducting this study. Additional thanks go to Dr. Ioannis Iossifidis, Sebastian Doliwa, Mehdi Cherbib, Clarissa Arlinghaus, Stefan Sommer and to all participants contributing to the study as well as to the reviewers.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Arntz, A., Eimler, S.C., Hoppe, H.U. (2020). Augmenting the Human-Robot Communication Channel in Shared Task Environments. In: Nolte, A., Alvarez, C., Hishiyama, R., Chounta, IA., Rodríguez-Triana, M., Inoue, T. (eds) Collaboration Technologies and Social Computing . CollabTech 2020. Lecture Notes in Computer Science(), vol 12324. Springer, Cham. https://doi.org/10.1007/978-3-030-58157-2_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-58157-2_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-58156-5
Online ISBN: 978-3-030-58157-2
eBook Packages: Computer ScienceComputer Science (R0)