Skip to main content
Log in

Effectiveness and acceptability of a virtual environment for assessing human–robot collaboration in manufacturing

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

A highly immersive and interactive virtual environment was constructed as an experimentation platform for human–robot collaboration in constricting panels from preimpregnated carbon fibre fabrics. The application involves highly collaborative tasks such as handover, removal of adhesive backing strip and fabric layup in a mould. Furthermore, the user is expected to be most of the time within the robot’s workspace, jointly working as teammates on collaborative manufacturing tasks. The environment embeds two interaction metaphors for complex tasks and advocates use of cognitive aids to cultivate proactive behaviour of the user, thus promoting situation awareness, danger perception and enrichment of communication between human and robot. The application was put under test by a group of users. Their experience was registered scholarly through questionnaires and objective observation and is reported in the paper to explore the effectiveness and acceptability of such an environment. Overall, the application was judged positively, especially the use of cognitive aids which, under circumstances turned into alarms and readily provided mental association of collision danger to its cause. Furthermore, some deficiencies were identified pertaining to lack of hand-tracking performance and need to improve the layup metaphor.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Krüger J, Lien TK, Verl A (2009) Cooperation of human and machines in assembly lines. CIRP Ann—Manuf Technol 58:628–646. doi:10.1016/j.cirp.2009.09.009

    Article  Google Scholar 

  2. Endsley MR (2011) Designing for situation awareness: an approach to user-centered design. CRC Press. 2nd edition, Boca Raton, ISBN 9781420063554

  3. Ogrinc M, Likar N, Petri T, et al (2011) Control and collision avoidance for two Kuka LWR robots operated with the Kinect sensor. In: Proc. RAAD 2011 20th Int. Work. Robot. Alpe-Adria-Danube Reg. Brno, Czech Republic, pp 5–10

  4. Fitzgerald C (2013). Developing baxter. In Proc. 2013 IEEE International Conference on Technologies for Practical Robot Applications (TePRA), IEEE, pp 1–6.

  5. Lenz C, Knoll A (2014) Mechanisms and capabilities for human robot collaboration. In: 23rd IEEE Int. Symp. Robot Hum. Interact. Commun. IEEE, pp 666–671

  6. Charalambous G, Fletcher SR, Webb P (2017) The development of a Human Factors Readiness Level tool for implementing industrial human-robot collaboration. Int J Adv Manuf Technol 1–11. doi: 10.1007/s00170-016-9876-6

  7. Robotic Industries Association (2012) ANSI/RIA R15. 06: 2012 Safety Requirements for industrial robots and robot systems. Ann Arbor: Robotic Industries Association

  8. ISO, ISO 10218-2: (2011): Robots and robotic devices–Safety requirements for industrial robots–Part 2: Robot systems and integration, Geneva, Switzerland: International Organization for Standardization 2011

  9. ISO, ISO 10218-1: (2011) Robots and Robotic Devices-Safety Requirements for Industrial Robots-Part 1: Robots. (2011) International Organization for Standardization, Geneva, Switzerland

  10. ISO, ISO/TS 15066:2016 (2016) Robots and robotic devices—collaborative robots, International Organization for Standardization, Geneva, Switzerland

  11. De Santis A, Siciliano B (2008) Safety issues for human-robot cooperation in manufacturing systems. VRTest 2008, Tools Perspect. Virtual Manuf

  12. Ikuta K, Ishii H, Nokata M (2003) Safety evaluation method of design and control for human-care robots. Int J Robot Res 22:281–297. doi:10.1177/0278364903022005001

    Article  Google Scholar 

  13. Fang HC, Ong SK, Nee AYC (2014) A novel augmented reality-based interface for robot path planning. Int J Interact Des Manuf 8:33–42. doi:10.1007/s12008-013-0191-2

    Article  Google Scholar 

  14. Hugues O, Weistroffer V, Paljic A, et al (2015) Determining the important subjective criteria in the perception of human-like robot movements using virtual reality. Int J Humanoid Robot 1550033. doi: 10.1142/S0219843615500334

  15. Kulić D, Croft E (2007) Pre-collision safety strategies for human-robot interaction. Auton Robots 22:149–164. doi:10.1007/s10514-006-9009-4

    Article  Google Scholar 

  16. Matsas E, Vosniakos G-C (2015) Design of a virtual reality training system for human–robot collaboration in manufacturing tasks. Int J Interact Des Manuf 1–15. doi: 10.1007/s12008-015-0259-2

  17. Chellali M-E-A (2009) Etude des interactions homme-homme pour l’elaboration du referentiel commun dans les environnements virtuels collaboratifs. Universite de Nantes

  18. Nonaka S, Inoue K, Arai T, Mae Y (2004) Evaluation of human sense of security for coexisting robots using virtual reality. 1st report: evaluation of pick and place motion of humanoid robots. In: IEEE Int. Conf. Robot. Autom. 2004. Proceedings. ICRA ‘04. 2004. IEEE, pp 2770–2775 Vol.3

  19. Takatalo J, Kawai T, Kaistinen J et al (2011) User experience in 3D stereoscopic games. Media Psychol 14:387–414. doi:10.1080/15213269.2011.620538

    Article  Google Scholar 

  20. Hoffman G, Breazeal C (2007) Effects of anticipatory action on human-robot teamwork efficiency, fluency, and perception of team. Proceeding ACM/IEEE Int Conf Human-robot Interact—HRI ‘07 1–8. doi: 10.1145/1228716.1228718

  21. Lasota PA, Shah JA (2015) Analyzing the effects of human-aware motion planning on close-proximity human-robot collaboration. Hum Factors J Hum Factors Ergon Soc 57:21–33. doi:10.1177/0018720814565188

    Article  Google Scholar 

  22. Wickens CD (2008) Situation awareness: review of Mica Endsley’s 1995 articles on situation awareness theory and measurement. Hum Factors 50:397–403. doi:10.1518/001872008X288420

    Article  Google Scholar 

  23. Huber M, Radrich H, Wendt C, et al (2009) Evaluation of a novel biologically inspired trajectory generator in human-robot interaction. In: Proc.—IEEE Int. Work. Robot Hum. Interact. Commun. pp 639–644

  24. Yamada Y, Hirasawa Y, Huang SY, Umetani Y (1996) Fail-safe human/robot contact in the safety space. In: Proc. 5th IEEE Int. Work. Robot Hum. Commun. RO-MAN’96 TSUKUBA. IEEE, pp 59–64

  25. Ogorodnikova O (2010) Human robot interaction: the safety challenge (an integrated frame work for human safety ), PhD dissertation. Budapest University of Technology and Economics, Faculty of Mechanical Engineering

  26. Haddadin S, Albu-Schaffer A, Hirzinger G (2009) Requirements for safe robots: measurements, analysis and new insights. Int J Robot Res 28:1507–1527. doi:10.1177/0278364909343970

    Article  Google Scholar 

  27. Ragaglia M, Bascetta L, Rocco P, Zanchettin AM (2014) Towards safe human-robot interaction: evaluating in real-time the severity of possible collisions in industrial scenarios. In: 7th Int. Work. Human-Friendly Robot. (HFR 2014), Oct. 23–24, 2014, Pontedera. p 2174

  28. Alami R, Gharbi M, Vadant B, et al (2014) On human-aware task and motion planning abilities for a teammate robot. Human-Robot Collab. Ind. Manuf. Work. RSS 2014

  29. Mori M, MacDorman K, Kageki N (2012) The Uncanny Valley [from the field]. IEEE Robot Autom Mag 19:98–100. doi:10.1109/MRA.2012.2192811

    Article  Google Scholar 

  30. Strassmair C, Taylor NK, Aylett R (2014) Human robot collaboration in production environments. 23rd IEEE Int. Symp. Robot Hum. Interact. Commun. RO-MAN 2014

  31. Vicentini F, Matthias B, Barattini P (2014) Industrial safety requirements for collaborative robots and applications. Eur. Robot. Forum—ERF 2014 Work. Saf. Ind. Robot. trends, Integr. Stand. 12–14 March 2014

  32. Bartneck C, Kulić D, Croft E, Zoghbi S (2009) Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. Int J Soc Robot 1:71–81. doi:10.1007/s12369-008-0001-3

    Article  Google Scholar 

  33. Duffy VG, Or CKL, Lau VWM (2006) Perception of safe robot speed in virtual and real industrial environments. Hum Factors Ergon Manuf 16:369–383

    Article  Google Scholar 

  34. Kulic D, Croft E (2007) Physiological and subjective responses to articulated robot motion. Robotica 25:13. doi:10.1017/S0263574706002955

    Article  Google Scholar 

  35. Kilteni K, Groten R, Slater M (2012) The sense of embodiment in virtual reality. Presence Teleoperators Virtual Environ 21:373–387. doi:10.1162/PRES_a_00124

    Article  Google Scholar 

  36. Booch G, Rumbaugh J, Jacobson I (2005) The unified modeling language user guide, 2nd edition. Addison-Wesley Professional ISBN: 0321267974

  37. Bowman DA, Kruijff E, LaViola JJ, Poupyrev I (2004) 3D user interfaces: theory and practice. Addison Wesley Longman Publishing Co., Inc., Redwood City

    Google Scholar 

  38. Matsas E, Vosniakos G, Batras D (2016) Modelling simple human-robot collaborative manufacturing tasks in interactive virtual environments. In: Proc. 2016 Virtual Real. Int. Conf.—VRIC ‘16. ACM Press, New York, New York, USA, pp 1–4

  39. Yang U, Kim GJ (2002) Implementation and evaluation of “just follow me”: an immersive, VR-based, motion-training system. Presence Teleoperators Virtual Environ 11:304–323. doi:10.1162/105474602317473240

    Article  Google Scholar 

  40. Ouramdane N, Otmane S, Davesne F, Mallem M (2006) FOLLOW-ME: a new 3D interaction technique based on virtual guides and granularity of interaction. In: Proc. 2006 ACM Int. Conf. Virtual real. Contin. Its Appl.—VRCIA ‘06. ACM Press, New York, p 137

    Google Scholar 

  41. Matsas E (2015) Development and assessment of interactive virtual reality models for robotic manufacturing systems design, PhD dissertation, national technical university of athens, school of mechanical engineering

  42. Endsley MR (1995) Toward a theory of situation awareness in dynamic systems. Hum Factors J Hum Factors Ergon Soc 37:65–84. doi:10.1518/001872095779049499

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to George-Christopher Vosniakos.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Matsas, E., Vosniakos, GC. & Batras, D. Effectiveness and acceptability of a virtual environment for assessing human–robot collaboration in manufacturing. Int J Adv Manuf Technol 92, 3903–3917 (2017). https://doi.org/10.1007/s00170-017-0428-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-017-0428-5

Keywords

Navigation