Zusammenfassung
Der Beitrag stellt die aktuelle, kollaborative Robotertechnologie vor und diskutiert sowohl Möglichkeiten als auch technische Hürden und Hemmnisse eines breiten Einsatzes. Er nimmt jeweils die Nutzer- und die Integrationsperspektive ein, um mögliche und wahrscheinliche Auswirkungen auf die vernetzten Arbeitswelt zu beleuchten. Aus der Nutzerperspektive sind dabei klassische Felder wie Usability und User Experience wichtig, aber es wird auch gezeigt, dass neue Fragen in der Kooperation mit Maschinen entstehen, beispielsweise wie Vertrauen etabliert werden kann. Aus der Integrationsperspektive wird aufgezeigt, dass mangelnde Wandlungsfähigkeit und fehlende digitale Integration große Hindernisse für den Einsatz von Robotern über die stark automatisierte Serienfertigung hinaus sind. Schließlich betrachtet der Beitrag insbesondere mittel- und längerfristige Wirkungen, die aus einer viel engeren Zusammenarbeit von Mensch und Roboter ausgehen können. Zusammenfassend wird festgestellt, dass sich sehr vielfältige Chancen und Risiken ergeben, die zahlreiche Herausforderungen insbesondere an die Arbeitsgestaltung darstellen. Denn moderne kollaborative Roboter sind nicht nur universale Werkzeuge zur Rationalisierung, sondern auch starkes Unterstützungsmittel für die Gestaltung menschzentrierter Assistenzsysteme.
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Adolphs, B., Bedenbender, H., Dirzus, D., Ehlich, M., Epple, U., Hankel, M., … Wollschlaeger, M. (2015). Statusreport. Referenzarchitekturmodell Industrie 4.0 (RAMI4.0). Düsseldorf: VDI. https://www.zvei.org/fileadmin/user_upload/Themen/Industrie_4.0/Das_Referenzarchitekturmodell_RAMI_4.0_und_die_Industrie_4.0-Komponente/pdf/Statusreport-Referenzmodelle-2015-v10.pdf. Zugegriffen am 03.02.2020.
Argall, B. D., Chernova, S., Veloso, M., & Browning, B. (2009). A survey of robot learning from demonstration. Robotics and Autonomous Systems, 57, 469–483. https://doi.org/10.1016/j.robot.2008.10.024.
Argote, L., Goodman, P. S., & Schkade, D. (1983). The human side of robotics: How workers react to a robot. Sloan Management Review, 24, 31–41.
Arthur, W., Jr., Bennett, W., Jr., Stanush, P. L., & McNelly, T. L. (1998). Factors that influence skill decay and retention: A quantitative review and analysis. Human Performance, 11, 57–101. https://doi.org/10.1207/s15327043hup1101_3.
Beer, J. M., Fisk, A. D., & Rogers, W. A. (2014). Toward a framework for levels of robot autonomy in human-robot interaction. Journal of Human-Robot Interaction, 3, 74–99. https://doi.org/10.5898/JHRI.3.2.Beer.
Bevan, N., Carter, J., Earthy, J., Geis, T., & Harker, S. (2016). New ISO standards for usability, usability reports and usability measures. In M. Kurosu (Hrsg.), Human-computer interaction. Theory, design, development and practice (S. 268–278). Cham: Springer. https://doi.org/10.1007/978-3-319-39510-4_25.
Busch, F., Thomas, C., Deuse, J., & Kuhlenkötter, B. (2012). A hybrid human-robot assistance system for welding operations – Methods to ensure process quality and forecast ergonomic conditions. In S. J. Hu (Hrsg.), Technologies and systems for assembly quality, productivity and customization – Proceedings of 4th CIRP conference on assembly technologies and systems (CATS) (S. 151–154).
Castro, B., Roberts, M., Mena, K., & Boerkoel, J. (2017). Who takes the lead? Automated scheduling for human-robot teams. Artificial Intelligence for Human-Robot Interaction, AAAI Technical Report FS-17-01, 85–89. https://www.cs.hmc.edu/HEAT/papers/Castro_et_al_AIHRI_2017.pdf. Zugegriffen am 03.02.2020.
Costescu, C. A., Vanderborght, B., & David, D. O. (2014). The effects of robot-enhanced psychotherapy: A meta-analysis. Review of General Psychology, 18, 127–136. https://doi.org/10.1037/gpr0000007.
Daimler. (2009). Mercedes-Benz Werk Untertürkheim: Leichtbauroboter im Piloteinsatz (Pressemitteilung). http://media.daimler.com/marsMediaSite/de/instance/ko.xhtml?oid=9907804. Zugegriffen am 03.02.2020.
Dauth, W., Findeisen, S., Südekum, J., & Wößner, N. (2017). German Robots: The impact of industrial Robots on workers (IAB-discussion paper No. 30/2017). Nürnberg. http://doku.iab.de/discussionpapers/2017/dp3017.pdf. Zugegriffen am 03.02.2020.
Diewald, M., Andernach, B., & Kunze, E. S. (2018). Entwicklung der Beschäftigungsstruktur durch Digitalisierung von Arbeit. In G. W. Maier, G. Engels & E. Steffen (Hrsg.), Handbuch Gestaltung digitaler und vernetzter Arbeitswelten. Berlin: Springer. https://doi.org/10.1007/978-3-662-52903-4_19-1.
Diftler, M. A., Mehling, J. S., Abdallah, M. E., Radford, N. A., Bridgwater, L. B., Sanders, A. M., … Ambrose, R. O. (2011). Robonaut 2 – The first humanoid robot in space. In 2011 IEEE International Conference on Robotics and Automation (ICRA) (S. 2178–2183). IEEE. https://doi.org/10.1109/ICRA.2011.5979830.
EFI – Expertenkommission Forschung und Innovation. (2016). Gutachten zu Forschung, Innovation und technologischer Leistungsfähigkeit Deutschlands 2016. Berlin: EFI. http://www.e-fi.de/fileadmin/Gutachten_2016/EFI_Gutachten_2016.pdf. Zugegriffen am 03.02.2020.
Endsley, M. R. (1995). Toward a theory of situation awareness in dynamic systems. Human Factors, 37, 32–64. https://doi.org/10.1518/001872095779049543.
Endsley, M. R. (2017). From here to autonomy: Lessons learned from human-automation research. Human Factors, 59, 5–27. https://doi.org/10.1177/0018720816681350.
Essig, K., Strenge, B., & Schack, T. (2018). Assistierende Technologie zur Förderung beruflichen Entwicklungspotenzials. In G. W. Maier, G. Engels & E. Steffen (Hrsg.), Handbuch Gestaltung digitaler und vernetzter Arbeitswelten. Berlin: Springer. https://doi.org/10.1007/978-3-662-52903-4_21-1.
Eyssel, F., & Hegel, F. (2012). (S)he’s got the look: Gender stereotyping of robots. Journal of Applied Social Psychology, 42, 2213–2230. https://doi.org/10.1111/j.1559-1816.2012.00937.x.
Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280. https://doi.org/10.1016/j.techfore.2016.08.019.
Gerber, T., Theorin, A., & Johnsson, C. (2014). Towards a seamless integration between process modeling descriptions at business and production levels: Work in progress. Journal of Intelligent Manufacturing, 25, 1089–1099. https://doi.org/10.1007/s10845-013-0754-x.
Gombolay, M. C., Gutierrez, R. A., Clarke, S. G., Sturla, G. F., & Shah, J. A. (2015). Decision-making authority, team efficiency and human worker satisfaction in mixed human-robot teams. Autonomous Robots, 39, 293–312. https://doi.org/10.1007/s10514-015-9457-9.
Gombolay, M., Bair, A., Huang, C., & Shah, J. (2017). Computational design of mixed-initiative human-robot teaming that considers human factors: Situational awareness, workload, and workflow preferences. The International Journal of Robotics Research, 36, 597–617. https://doi.org/10.1177/0278364916688255.
Gopinathan, S., Ötting, S., & Steil, J. J. (2017). A user study on personalized stiffness control and task specificity in physical human-robot interaction. Frontiers in Robotics and AI, 4, 58. https://doi.org/10.3389/frobt.2017.00058.
Haddadin, S., Albu-Schäffer, A., & Hirzinger, G. (2009). Requirements for safe robots: Measurements, analysis and new insights. The International Journal of Robotics Research, 28, 1507–1527. https://doi.org/10.1177/0278364909343970.
Hamilton, A. D. C., Joyce, D. W., Flanagan, J. R., Frith, C. D., & Wolpert, D. M. (2007). Kinematic cues in perceptual weight judgement and their origins in box lifting. Psychological Research, 71, 13–21. https://doi.org/10.1007/s00426-005-0032-4.
Hancock, P. A., Billings, D. R., Schaefer, K. E., Chen, J. Y. C., de Visser, E. J., & Parasuraman, R. (2011). A meta-analysis of factors affecting trust in human-robot interaction. Human Factors, 53, 517–527. https://doi.org/10.1177/0018720811417254.
Heinze, F., Klöckner, M., Wantia, N., Rossmann, J., Kuhlenkötter, B., & Deuse, J. (2016). Combining planning and simulation to create human robot cooperative processes with industrial service robots. Applied Mechanics & Materials, 840, 91–98. https://doi.org/10.4028/www.scientific.net/AMM.840.91.
Herold, D. M., Farmer, S. M., & Mobley, M. I. (1995). Pre-implementation attitudes toward the introduction of robots in a unionized environment. Journal of Engineering and Technology Management, 12, 155–173. https://doi.org/10.1016/0923-4748(95)00008-7.
International Federation of Robotics (IFR). (2019). Executive summary World Robotics 2019 Industrial Robots. https://ifr.org/downloads/press2018/Executive%20Summary%20WR%202019%20Industrial%20Robots.pdf. Zugegriffen am 14.02.2020.
Ishiguro, H., Ono, T., Imai, M., Maeda, T., Kanda, T., & Nakatsu, R. (2001). Robovie: An interactive humanoid robot. Industrial Robot: An International Journal, 28, 498–504. https://doi.org/10.1108/01439910110410051.
Kaber, D. B., Onal, E., & Endsley, M. R. (2000). Design of automation for telerobots and the effect on performance, operator situation awareness, and subjective workload. Human Factors and Ergonomics in Manufacturing, 10, 409–430.
Kanda, T., Hirano, T., Eaton, D., & Ishiguro, H. (2004). Interactive robots as social partners and peer tutors for children: A field trial. Human-Computer Interaction, 19, 61–84. https://doi.org/10.1207/s15327051hci1901&2_4.
Kanero, J., Geçkin, V., Oranç, C., Mamus, E., Küntay, A. C., & Göksun, T. (2018). Social robots for early language learning: Current evidence and future directions. Child Development Perspectives, 12(3), 146–151. https://doi.org/10.1111/cdep.12277.
Kirstein, F., Fischer, K., & Solvason, D. (2014). Human embodiment creates problems for robot learning by demonstration using a control panel. In Proceedings of the 2014 ACM/IEEE international conference on human-robot interaction (S. 212–213). https://doi.org/10.1145/2559636.2563713.
Kluge, A., Frank, B., & Miebach, J. (2013). Measuring skill decay in process control-results from four experiments with a simulated process control task. In D. de Waard, K. Brookhuis, R. Wiczorek, F. di Nocera, R. Brouwer, P. Barham, … A. Toffetti (Hrsg.), Proceedings of the human factors and ergonomics society Europe chapter 2013 annual conference (S. 79–93).
Kormushev, P., Calinon, S., & Caldwell, D. G. (2011). Imitation learning of positional and force skills demonstrated via kinesthetic teaching and haptic input. Advanced Robotics, 25, 581–603. https://doi.org/10.1163/016918611X558261.
Krach, S., Hegel, F., Wrede, B., Sagerer, G., Binkofski, F., & Kircher, T. (2008). Can machines think? Interaction and perspective taking with robots investigated via fMRI. PLoS One, 3(7), e2597. https://doi.org/10.1371/journal.pone.0002597.
Kröger, T., Finkemeyer, B., & Wahl, F. M. (2010). Manipulation primitives – A universal interface between sensor-based motion control and robot programming. In D. Schütz & F. M. Wahl (Eds.), Robotic systems for handling and assembly (Springer tracts in advanced robotics, Bd. 67 // STAR 67, S. 293–313). Berlin: Springer. https://doi.org/10.1007/978-3-642-16785-0_17.
Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors, 46, 50–80. https://doi.org/10.1518/hfes.46.1.50_30392.
Lee, J., Bagheri, B., & Kao, H.-A. (2015). A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manufacturing Letters, 3, 18–23. https://doi.org/10.1016/j.mfglet.2014.12.001.
Lin, S.-W., Mellor, S., Miller, B., Durand, J., Crawford, M., & Lembree, R. (Hrsg.). (2015). Industrial internet reference architecture, Version 1.7. Industrial Internet Consortium. https://www.iiconsortium.org/IIRA-1-7-ajs.pdf. Zugegriffen am 03.02.2020.
MacDougall, W. (2014). Industrie 4.0: Smart manufacturing for the future. Berlin: Germany Trade and Invest, July 2014. https://www.manufacturing-policy.eng.cam.ac.uk/documents-folder/policies/germany-industrie-4-0-smart-manufacturing-for-the-future-gtai/view. Zugegriffen am 03.02.2020.
Mason, M. & Lopes, M. (2011). Robot self-initiative and personalization by learning through repeated interactions. In 2011 6th ACM/IEEE international conference on human-robot interaction (S. 433–440). IEEE. https://doi.org/10.1145/1957656.1957814.
Mlekus, L., Ötting, S. K., & Maier, G. W. (2018). Psychologische Arbeitsgestaltung digitaler Arbeitswelten. In G. W. Maier, G. Engels & E. Steffen (Hrsg.), Handbuch Gestaltung digitaler und vernetzter Arbeitswelten. Berlin: Springer. https://doi.org/10.1007/978-3-662-52903-4_5-1.
Murashov, V., Hearl, F., & Howard, J. (2016). Working safely with robot workers: Recommendations for the new workplace. Journal of Occupational and Environmental Hygiene, 13, D61–D71. https://doi.org/10.1080/15459624.2015.1116700.
Nisen, M. (2014). Toyota is becoming more efficient by replacing robots with humans. Quartz. https://qz.com/196200/toyota-is-becoming-more-efficient-by-replacing-robots-with-humans/. Zugegriffen am 07.04.2014.
Ötting, S., Gopinathan, S., Maier, G. W., & Steil, J. J. (2017). Why criteria of decision fairness should be considered in robot design. Presented at the CSCW 2017: The 20th ACM Conference on Computer-Supported Cooperative Work and Social Computing, Portland.
Redden, E. S., Elliott, L. R., & Barnes, M. J. (2014). Robots: The new teammates. In M. D. Coovert & L. F. Thompson (Hrsg.), The psychology of workplace technology (S. 185–208). New York: Routledge.
Ritter, H., Haschke, R., & Steil, J. J. (2007). A dual interaction perspective for robot cognition: Grasping as a „Rosetta Stone“. In B. Hammer & P. Hitzler (Hrsg.), Perspectives of neural-symbolic integration. Studies in computational intelligence (Bd. 77, S. 159–178). Berlin: Springer. https://doi.org/10.1007/978-3-540-73954-8_7.
Robotiq. (2016). Collaborative robot ebook. http://blog.robotiq.com/collaborative-robot-ebook. Zugegriffen am 30.06.2016.
Roether, C. L., Omlor, L., Christensen, A., & Giese, M. A. (2009). Critical features for the perception of emotion from gait. Journal of Vision, 9, 1–32. https://doi.org/10.1167/9.6.15.
Salem, M., Eyssel, F., Rohlfing, K. J., Kopp, S., & Joublin, F. (2013). To err is human(-like): Effects of robot gesture on perceived anthropomorphism and likability. International Journal of Social Robotics, 5, 313–323. https://doi.org/10.1007/s12369-013-0196-9.
Shibata, T. (2004). An overview of human interactive robots for psychological enrichment. Proceedings of the IEEE, 92(11), 1749–1758.
Slama, D., Puhlmann, F., Morrish, J., & Bhatnagar, R. M. (2015). Enterprise IoT: Strategies and best practices for connected products and services. Sebastopol, CA: O’Reilly.
Steil, J. J., & Krüger, S. (2013). Lernen und Sicherheit in Interaktion mit Robotern aus Maschinensicht. In J.-P. Günther & E. Hilgendorf (Hrsg.), Robotik und Gesetzgebung (S. 51–73). Baden-Baden: Nomos. https://doi.org/10.5771/9783845242200-51.
Steil, J. J., & Maier, G. W. (2017). Robots in the digitalized workplace. In G. Hertel, D. Stone, R. Johnson & J. Passmore (Hrsg.), The Wiley Blackwell handbook of the psychology of the internet at work (S. 403–422). Chichester: Wiley-Blackwell.
Tay, B., Jung, Y., & Park, T. (2014). When stereotypes meet robots: The double-edge sword of robot gender and personality in human-robot interaction. Computers in Human Behavior, 38, 75–84. https://doi.org/10.1016/j.chb.2014.05.014.
Villani, L., & De Schutter, J. (2008). Force control. In B. Siciliano & O. Khatib (Hrsg.), Springer handbook of robotics (S. 161–185). Berlin: Springer. https://doi.org/10.1007/978-3-540-30301-5_8.
Vollmer, A.-L., Lohan, K. S., Fischer, K., Nagai, Y., Pitsch, K., Fritsch, … Wrede, B. (2009). People modify their tutoring behavior in robot-directed interaction for action learning. In 2009 IEEE 8th international conference on development and learning (S. 1–6). IEEE. https://doi.org/10.1109/DEVLRN.2009.5175516.
Vollmer, A.-L., Mühlig, M., Steil, J. J., Pitsch, K., Fritsch, J., Rohlfing, K. J., & Wrede, B. (2014). Robots show us how to teach them: Feedback from robots shapes tutoring behavior during action learning. PLoS One, 9, e91349. https://doi.org/10.1371/journal.pone.0091349.
Wallhoff, F., Blume, J., Bannat, A., Rösel, W., Lenz, C., & Knoll, A. (2010). A skill-based approach towards hybrid assembly. Advanced Engineering Informatics, 24, 329–339. https://doi.org/10.1016/j.aei.2010.05.013.
Weyer, J. (2007). Ubiquitous Computing und die neue Arbeitswelt. In K. Kornwachs (Hrsg.), Bedingungen und Triebkräfte technologischer Innovationen (S. 199–214). Stuttgart: Fraunhofer IRB Verlag.
Wrede, S., Emmerich, C., Grünberg, R., Nordmann, A., Swadzba, A., & Steil, J. (2013). A user study on kinesthetic teaching of redundant robots in task and configuration space. Journal of Human-Robot Interaction, 2, 56–81. https://doi.org/10.5898/JHRI.2.1.Wrede.
Wrede, S., Beyer, O., Dreyer, C., Wojtynek, M., & Steil, J. J. (2016). Vertical integration and service orchestration for modular production systems using business process models. Paper presented at the 3rd international conference on system-integrated intelligence: New challenges for product and production engineering, Paderborn.
Wurhofer, D., Meneweger, T., Fuchsberger, V., & Tscheligi, M. (2015). Deploying robots in a production environment: A study on temporal transitions of workers’ experiences. In J. Abascal, S. Barborsa, M. Fetter, T. Gross, P. Palanque & M. Winkler (Hrsg.), Human-computer interaction – INTERACT 2015 (Part III, S. 203–220). Heidelberg: Springer. https://doi.org/10.1007/978-3-319-22698-9_14.
Yang, C., Ganesh, G., Haddadin, S., Parusel, S., Albu-Schäffer, A., & Burdet, E. (2011). Human-like adaptation of force and impedance in stable and unstable interactions. IEEE Transactions on Robotics, 27(5), 918–930. https://doi.org/10.1109/TRO.2011.2158251.
You, S., & Robert, L. P. (2017). Teaming up with robots: An IMOI (Inputs-Mediators-Outputs-Inputs) framework of human-robot teamwork. International Journal of Robotic Engineering, 2(003).
Young, S. M., & Davis, J. S. (1990). Factories of the past and of the future: The impact of robotics on workers and management accounting systems. In D. J. Cooper & T. M. Hopper (Hrsg.), Critical accounts (S. 87–106). London: Palgrave.
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Steil, J.J., Maier, G.W. (2020). Kollaborative Roboter: universale Werkzeuge in der digitalisierten und vernetzten Arbeitswelt. In: Maier, G., Engels, G., Steffen, E. (eds) Handbuch Gestaltung digitaler und vernetzter Arbeitswelten. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-52979-9_15
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