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Collaborative Patterns for Workflows with Collaborative Robots

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Cooperative Information Systems (CoopIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13591))

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Abstract

Collaborative work environments have gained more attention in manufacturing in recent years, in particular with the development of collaborative robots (cobots), a special type of industrial robot that is built for the safe interaction between humans and robots. Recent advances have shown that there are several collaboration scenarios between humans and robots, such as, synchronized, cooperation, collaboration and coexistence. So far, most literature focuses only on the collaboration between one human and one robot. However, literature also predicts that there will be more collaboration scenarios with one or many humans collaborating with one or many robots. Furthermore, literature on collaboration scenarios often focuses only on a generic process perspective and does not detail tasks nor other aspects. In this paper, we aim to address these gaps by investigating collaboration scenarios for one to many and many to many relations between robots and humans in workflows. First, we formalize the collaboration pattern and its types (synchronized, cooperation, collaboration and coexistence). Our approach allows for the specification of time-based, spatial and functional constraints at task level in collaborative work environments. Second, we demonstrate our findings with a proof-of-concept implementation that consists of a workflow system, a cobot simulation and a communication and data platform. Third, we evaluate our model with altogether seven use cases (e.g., spot taping). The results show that the patterns can be applied for the specification of collaboration scenarios in modern, process-oriented work environments. For future work, we would like to investigate questions on process modeling and visualization of collaborative patterns.

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Notes

  1. 1.

    https://github.com/etm/opcua-smart (visited on June 8, 2022).

  2. 2.

    See a full set of use cases including the full BPMN diagram of the use case spot taping at https://tinyurl.com/yskk989s.

References

  1. van der Aalst, W.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer, Germany (2011). https://doi.org/10.1007/978-3-642-19345-3

  2. Bi, Z., Luo, C., Miao, Z., Zhang, B., Zhang, W., Wang, L.: Safety assurance mechanisms of collaborative robotic systems in manufacturing. Robot. Comput. Integr. Manuf. 67, 102022 (2021)

    Article  Google Scholar 

  3. Bonitasoft, S.A.: Bonita Documentation. https://documentation.bonitasoft.com/bonita/2021.2/. Accessed 10 Feb 2021

  4. Buerkle, A., Eaton, W., Lohse, N., Bamber, T., Ferreira, P.: EEG based arm movement intention recognition towards enhanced safety in symbiotic human-robot collaboration. Robot. Comput. Integr. Manuf. 70, 102137 (2021)

    Article  Google Scholar 

  5. Cherubini, A., Passama, R., Fraisse, P., Crosnier, A.: A unified multimodal control framework for human-robot interaction. Robot. Auton. Syst. 70, 106–115 (2015)

    Article  Google Scholar 

  6. Chua, Y., Tee, K.P., Yan, R.: Human-robot motion synchronization using reactive and predictive controllers. In: 2010 IEEE International Conference on Robotics and Biomimetics, pp. 223–228 (12 2010)

    Google Scholar 

  7. Dumonteil, G., Manfredi, G., Devy, M., Confetti, A., Sidobre, D.: Reactive planning on a collaborative robot for industrial applications. In: 2015 12th International Conference on Informatics in Control, Automation and Robotics (ICINCO), vol. 02, pp. 450–457 (2015)

    Google Scholar 

  8. Eder, J., Panagos, E., Rabinovich, M.: Time constraints in workflow systems. In: Jarke, M., Oberweis, A. (eds.) CAiSE 1999. LNCS, vol. 1626, pp. 286–300. Springer, Heidelberg (1999). https://doi.org/10.1007/3-540-48738-7_22

    Chapter  Google Scholar 

  9. El Makrini, I., Merckaert, K., Lefeber, D., Vanderborght, B.: Design of a collaborative architecture for human-robot assembly tasks. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1624–1629 (2017)

    Google Scholar 

  10. El Makrini, I., et al.: Design and investigation of social robotic coworkers in factories, pp. 1–2. IEEE (2017)

    Google Scholar 

  11. El Zaatari, S., Marei, M., Li, W., Usman, Z.: Cobot programming for collaborative industrial tasks: an overview. Robot. Auton. Syst. 116, 162–180 (2019)

    Article  Google Scholar 

  12. Fdhila, W., Gall, M., Rinderle-Ma, S., Mangler, J., Indiono, C.: Classification and formalization of instance-spanning constraints in process-driven applications. In: La Rosa, M., Loos, P., Pastor, O. (eds.) BPM 2016. LNCS, vol. 9850, pp. 348–364. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-45348-4_20

    Chapter  Google Scholar 

  13. Froschauer, R., Lindorfer, R.: Workflow-based programming of human-robot interaction for collaborative assembly stations. In: Proceedings of ARW & OAGM Workshop 2019, pp. 85–90 (2019)

    Google Scholar 

  14. Hermann, A., Mauch, F., Fischnaller, K., Klemm, S., Roennau, A., Dillmann, R.: Anticipate your surroundings: predictive collision detection between dynamic obstacles and planned robot trajectories on the GPU. In: 2015 European Conference on Mobile Robots (ECMR), pp. 1–8 (2015)

    Google Scholar 

  15. International Federation of Robotics: Demystifying collaborative industrial robots. Frankfurt, Germany (2018). https://ifr.org/papers/demystifying-collaborative-industrial-robots-updated-version. Accessed 12 June 2022

  16. Jiang, Y., Yu, L., Jia, H., Zhao, H., Xia, H.: Absolute positioning accuracy improvement in an industrial robot. Sensors 20(16), 4354 (2020)

    Article  Google Scholar 

  17. Knuplesch, D., Reichert, M., Pryss, R., Fdhila, W., Rinderle-Ma, S.: Ensuring compliance of distributed and collaborative workflows. In: 9th IEEE International Conference on Collaborative Computing, pp. 133–142 (2013)

    Google Scholar 

  18. Kopp, T., Baumgartner, M., Kinkel, S.: Success factors for introducing industrial human-robot interaction in practice: an empirically driven framework. Int. J. Adv. Manuf. Technol. 112(3), 685–704 (2020). https://doi.org/10.1007/s00170-020-06398-0

    Article  Google Scholar 

  19. Krüger, J., Lien, T., Verl, A.: Cooperation of human and machines in assembly lines. CIRP Ann. 58(2), 628–646 (2009)

    Article  Google Scholar 

  20. Kumar, A., Sabbella, S.R., Barton, R.R.: Managing controlled violation of temporal process constraints. In: Motahari-Nezhad, H.R., Recker, J., Weidlich, M. (eds.) BPM 2015. LNCS, vol. 9253, pp. 280–296. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23063-4_20

    Chapter  Google Scholar 

  21. Leitner, M., Mangler, J., Rinderle-Ma, S.: Definition and enactment of instance-spanning process constraints. In: Wang, X.S., Cruz, I., Delis, A., Huang, G. (eds.) WISE 2012. LNCS, vol. 7651, pp. 652–658. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-35063-4_49

    Chapter  Google Scholar 

  22. Lichiardopol, S., van de Wouw, N., Nijmeijer, H.: Control scheme for human-robot co-manipulation of uncertain, time-varying loads. In: 2009 American Control Conference, pp. 1485–1490 (2009). https://doi.org/10.1109/ACC.2009.5160062

  23. Malik, A.A., Brem, A.: Digital twins for collaborative robots: a case study in human-robot interaction. Robot. Comput. Integr. Manuf. 68, 102092 (2021). https://doi.org/10.1016/j.rcim.2020.102092

    Article  Google Scholar 

  24. Matheson, E., Minto, R., Zampieri, E.G.G., Faccio, M., Rosati, G.: Human-robot collaboration in manufacturing applications: a review. Robotics 8(4), 100 (2019). https://doi.org/10.3390/robotics8040100

    Article  Google Scholar 

  25. Müller, R., Vette, M., Geenen, A.: Skill-based dynamic task allocation in human-robot-cooperation with the example of welding application. Procedia Manuf. 11, 13–21 (2017). https://doi.org/10.1016/j.promfg.2017.07.113. 27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM2017, 27–30 June 2017, Modena, Italy

  26. Müller, R., Vette, M., Mailahn, O.: Process-oriented task assignment for assembly processes with human-robot interaction. Procedia CIRP 44, 210–215 (2016). https://doi.org/10.1016/j.procir.2016.02.080. 6th CIRP Conference on Assembly Technologies and Systems (CATS)

  27. OPC Foundation: What is OPC?. https://opcfoundation.org/about/what-is-opc/. Accessed 23 Nov 2021

  28. Román Ibáñez, V., Pujol, F., García Ortega, S., Sanz Perpiñán, J.: Collaborative robotics in wire harnesses spot taping process. Comput. Ind. 125, 103370 (2021). https://doi.org/10.1016/j.compind.2020.103370

    Article  Google Scholar 

  29. Samadikhoshkho, Z., Zareinia, K., Janabi-Sharifi, F.: A brief review on robotic grippers classifications. In: 2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE), pp. 1–4 (2019). https://doi.org/10.1109/CCECE.2019.8861780

  30. Schmidbauer, C., Hader, B., Schlund, S.: Evaluation of a digital worker assistance system to enable adaptive task sharing between humans and Cobots in manufacturing. Procedia CIRP 104, 38–43 (2021)

    Article  Google Scholar 

  31. Schneider, G., Wendl, M., Kucek, S., Leitner, M.: A training concept based on a digital twin for a wafer transportation system. In: 2021 IEEE 23rd Conference on Business Informatics (CBI), vol. 02, pp. 20–28 (2021)

    Google Scholar 

  32. Steinau, S., Andrews, K., Reichert, M.: Modeling process interactions with coordination processes. In: Panetto, H., Debruyne, C., Proper, H.A., Ardagna, C.A., Roman, D., Meersman, R. (eds.) OTM 2018. LNCS, vol. 11229, pp. 21–39. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-02610-3_2

    Chapter  Google Scholar 

  33. The Robot Report Staff: Scoliobot aims to improve spinal surgery accuracy. https://www.therobotreport.com/scoliobot-spinal-surgery-accuracy/. Accessed 13 Apr 2021

  34. Tlach, V., Cisar, M., Kuric, I., Zajacko, I.: Determination of the industrial robot positioning performance. In: MATEC Web of Conferences, vol. 137 (2017)

    Google Scholar 

  35. Universal Robots A/S: An introduction to common collaborative robot applications. https://info.universal-robots.com/hubfs/Enablers/White%20papers/Common%20Cobot%20%20Applications.pdf. Accessed 15 Nov 2021

  36. Universal Robots A/S: Offline simulator - e-series - ur sim for linux 5.11.5. https://www.universal-robots.com/download/software-e-series/simulator-linux/offline-simulator-e-series-ur-sim-for-linux-5115/. Accessed 16 Nov 2021

  37. Wang, L., et al.: Symbiotic human-robot collaborative assembly. CIRP Ann. 68(2), 701–726 (2019)

    Article  Google Scholar 

  38. Wang, X.V., Kemény, Z., Váncza, J., Wang, L.: Human-robot collaborative assembly in cyber-physical production: classification framework and implementation. CIRP Ann. 66(1), 5–8 (2017)

    Article  Google Scholar 

  39. Weichhart, G., et al.: An adaptive system-of-systems approach for resilient manufacturing. e & i Elektrotechnik und Informationstechnik 138(6), 341–348 (2021)

    Google Scholar 

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Authors and Affiliations

  1. University of Vienna, Faculty of Computer Science, Research Group Workflow Systems and Technology, Vienna, Austria

    Stefan Samhaber & Maria Leitner

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  1. Stefan Samhaber
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  2. Maria Leitner
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Correspondence to Maria Leitner .

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Editors and Affiliations

  1. Telecom SudParis - Institut Polytechnique de Paris, Evry, France

    Mohamed Sellami

  2. University of Milan, Milan, Italy

    Paolo Ceravolo

  3. Utrecht University, Utrecht, The Netherlands

    Hajo A. Reijers

  4. Telecom SudParis - Institut Polytechnique de Paris, Evry, France

    Walid Gaaloul

  5. University of Lorraine, Vandoeuvre-les-Nancy, France

    Hervé Panetto

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Samhaber, S., Leitner, M. (2022). Collaborative Patterns for Workflows with Collaborative Robots. In: Sellami, M., Ceravolo, P., Reijers, H.A., Gaaloul, W., Panetto, H. (eds) Cooperative Information Systems. CoopIS 2022. Lecture Notes in Computer Science, vol 13591. Springer, Cham. https://doi.org/10.1007/978-3-031-17834-4_8

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  • DOI: https://doi.org/10.1007/978-3-031-17834-4_8

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