Skip to main content

Evaluating Team Fluency in Human-Industrial Robot Collaborative Design Tasks

  • Conference paper
  • First Online:
Computer-Aided Architectural Design. Design Imperatives: The Future is Now (CAAD Futures 2021)

Abstract

Trust, reliance, and robustness have been identified as key elements for team fluency between teams. They are also crucial elements for successful collaboration between humans and robots (HRC). Robot arms have become integral to numerous digital design and fabrication processes allowing new material forms, more efficient use of materials and novel geometries. It will not be long before close proximity HRC design becomes standard. However, little research has been directed at understanding team fluency development between industrial robots and humans (industrial HRC). Even less to understand the evolution of HRC in creative tasks and factors that influence elements like trust to be established between industrial robot arms and designers. Team fluency is a multidimensional construct, heavily dependent on the context. It is crucial to understand how team fluency develops when designers interact with industrial robots. To this end, in this study, a team fluency measurement scale suitable for industrial HRC in design activities was developed in two stages. In the first stage, HRC literature was reviewed to establish a measurement scale for the different team fluency constructs and identify team fluency-related themes relevant to the design context. A corresponding pool of questionnaire items was generated. In the second stage, an exploratory HRC design exercise was designed and conducted to collect participant’s opinions qualitatively and quantitative. Questionnaire items were applied to participants. The results were statistically analyzed to identify the key factors impacting team fluency. A set of curriculum recommendations is made, and a team fluency scale is proposed to measure HRC in design activities.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Hoffman, G.: Evaluating fluency in human–robot collaboration. IEEE Trans. Hum.-Mach. Syst. 1–10 (2019). https://doi.org/10.1109/THMS.2019.2904558

  2. Hoffman, G.: Evaluating fluency in human-robot collaboration. HRI Work. Hum. Robot Collab. 2013 (2013)

    Google Scholar 

  3. Hoffman, G.: Evaluating fluency in human-robot collaboration. Robot. Sci. Syst. Work. Hum. Robot Collab. 381, 1–8 (2013)

    Google Scholar 

  4. Hoffman, G., Breazeal, C.: Cost-based anticipatory action selection for human-robot fluency. IEEE Trans. Robot. 23, 952–961 (2007). https://doi.org/10.1109/TRO.2007.907483

    Article  Google Scholar 

  5. Merriam-Webster: Merriam - Webster dictionary. http://www.merriam-webster.com/dictionary/teamwork

  6. Groom, V., Nass, C.: Can robots be teammates? Benchmarks in human-robot teams. Interact. Stud. 8, 483–500 (2007). https://doi.org/10.1075/gest.8.3.02str

    Article  Google Scholar 

  7. Gao, F., Cummings, M.L., Solovey, E.: Designing for robust and effective teamwork in human-agent teams. In: Mittu, R., Sofge, D., Wagner, A., Lawless, W.F. (eds.) Robust Intelligence and Trust in Autonomous Systems, pp. 167–190. Springer, Boston (2016). https://doi.org/10.1007/978-1-4899-7668-0_9

    Chapter  Google Scholar 

  8. Joe, J.C., O’Hara, J., Hugo, J.V., Oxstrand, J.H.: Function allocation for humans and automation in the context of team dynamics. Procedia Manuf. 3, 1225–1232 (2015). https://doi.org/10.1016/j.promfg.2015.07.204

    Article  Google Scholar 

  9. Dickinson, T.L., McIntyre, R.M.: A conceptual framework for teamwork measurement. In: Team Performance Assessment and Measurement: Theory, Methods, and Applications, pp. 19–43. Lawrence Erlbaum Associates Publishers, Mahwah (1997)

    Google Scholar 

  10. Larson, C.E., LaFasto, F.M.J.: Teamwork: What Must Go Right, What Can Go Wrong. Sage Publications, Newbury Park (1989)

    Google Scholar 

  11. Licklider J.C.R.: Man-computer symbiosis. IRE Trans. Hum. Factors Electron. HFE-1, 4–11 (1960)

    Google Scholar 

  12. Charalambous, G.: The development of a human factors tool for the successful implementation of industrial human-robot collaboration (2014)

    Google Scholar 

  13. Horvath, A.O., Greenberg, L.S.: Development and validation of the working alliance inventory. J. Couns. Psychol. 36, 223–233 (1989)

    Article  Google Scholar 

  14. Lee, J., Moray, N.: Trust, control strategies and allocation of function in human-machine systems (1992). https://doi.org/10.1080/00140139208967392

  15. Lee, J.D., See, K.A., City, I.: Trust in automation: designing for appropriate reliance. Hum. Factors Ergon. Soc. 46, 50–80 (2004)

    Article  Google Scholar 

  16. Kruijff, G.-J., Janıcek, M.: Using doctrines for human-robot collaboration to guide ethical behavior. In: AAAI Fall Symposium: Robot-Human Teamwork in Dynamic Adverse Environment, pp. 26–33 (2011)

    Google Scholar 

  17. Terveen, L.G.: Overview of human-computer collaboration. Knowl.-Based Syst. 8, 67–81 (1995). https://doi.org/10.1016/0950-7051(95)98369-H

    Article  Google Scholar 

  18. Johns, R.L.: Augmented materiality modelling with material indeterminacy. In: Fabricate: Making Digital Architecture, pp. 216–223 (2014)

    Google Scholar 

  19. Macmillan, J., Entin, E.E., Serfaty, D.: Communication Overhead: The Hidden Cost of Team Cognition, Washington, DC (2004). https://doi.org/10.1080/03637759309376288

  20. Nahmad Vazquez, A.: Robotic Assisted Design: A study of key human factors influencing team fluency in human‐robot collaborative design processes (2019)

    Google Scholar 

  21. Nicholas, P., et al.: Adaptive robotic fabrication for conditions of material inconsistency. In: Fabricate 2017, pp. 114–121 (2017)

    Google Scholar 

  22. Nahmad Vazquez, A., Jabi, W.: Robotic assisted design workflows: a study of key human factors influencing team fluency in human-robot collaborative design processes. Archit. Sci. Rev. 1–15 (2019). https://doi.org/10.1080/00038628.2019.1660611

  23. Wright, P., McCarthy, J.: The politics and aesthetics of participatory HCI. Interactions 22, 26–31 (2015). https://doi.org/10.1145/2828428

    Article  Google Scholar 

  24. Onwuegbuzie, A.J., Leech, N.L., Collins, K.M.T.: Qualitative analysis techniques for the review of the literature. Qual. Rep. 17, 1–28 (2012)

    Google Scholar 

  25. Braun, V., Clarke, V.: Using thematic analysis in psychology. Qual. Res. Psychol. 3, 77–101 (2006)

    Article  Google Scholar 

  26. King, N.: Template analysis. In: Symon, G., Cassell, C. (eds.) Qualitative Methods and Analysis in Organizational Research, pp. 118–134. SAGE Publications, Michigan (1998)

    Google Scholar 

  27. Kline, P.: The Handbook of Psychological Testing. Routledge, Milton Park (2000)

    Google Scholar 

  28. Kulić, D., Croft, E.: Physiological and subjective responses to articulated robot motion. Robotica 25, 13–27 (2007). https://doi.org/10.1017/S0263574706002955

    Article  Google Scholar 

  29. Kline, T.: Psychological Testing: A Practical Approach to Design and Evaluation (2005). https://methods.sagepub.com/book/psychological-testing. https://doi.org/10.4135/9781483385693

  30. Loewenthal, K.M.: An Introduction to Psychological Tests and Scales. UCL Press Limited, London (1996)

    Google Scholar 

  31. Maxwell, S.E., Delaney, H.D.: Designing Experiments and Analyzing Data: A Model Comparison Perspective. Psychology Press, New York (2004)

    MATH  Google Scholar 

  32. Hoffman, G., Breazeal, C.: Effects of anticipatory perceptual simulation on practiced human-robot tasks. Auton. Robots. 28, 403–423 (2010). https://doi.org/10.1007/s10514-009-9166-3

    Article  Google Scholar 

  33. van den Brule, R., Dotsch, R., Bijlstra, G., Wigboldus, D.H.J., Haselager, P.: Do robot performance and behavioral style affect human trust? Int. J. Soc. Robot. 6(4), 519–531 (2014). https://doi.org/10.1007/s12369-014-0231-5

    Article  Google Scholar 

  34. Hancock, P.A., Billings, D.R., Schaefer, K.E., Chen, J.Y.C., De Visser, E.J., Parasuraman, R.: A meta-analysis of factors affecting trust in human-robot interaction. Hum. Factors. 53, 517–527 (2011). https://doi.org/10.1177/0018720811417254

    Article  Google Scholar 

  35. Charalambous, G., Fletcher, S., Webb, P.: The development of a scale to evaluate trust in industrial human-robot collaboration. Int. J. Soc. Robot. 8(2), 193–209 (2015). https://doi.org/10.1007/s12369-015-0333-8

    Article  Google Scholar 

  36. Bartneck, C., Kulic, D., Croft, E.: Measuring instruments for the anthropomorhism, animacy, likeability, perceived intelligence, and perceived safety of robots. Int. J. Soc. Robot. 1, 71–81 (2009). https://doi.org/10.1007/s12369-008-0001-3

    Article  Google Scholar 

  37. Broadbent, E., Stafford, R., MacDonald, B.: Acceptance of healthcare robots for the older population: review and future directions. Int. J. Soc. Robot. 1, 319–330 (2009). https://doi.org/10.1007/s12369-009-0030-6

    Article  Google Scholar 

  38. Rau, P.L.P., Li, Y., Li, D.: A cross-cultural study: effect of robot appearance and task. Int. J. Soc. Robot. 2, 175–186 (2010). https://doi.org/10.1007/s12369-010-0056-9

    Article  Google Scholar 

  39. Saerbeck, M., Bartneck, C.: Perception of affect elicited by robot motion. In: Proceeding 5th ACM/IEEE International Conference on Human-Robot Interaction - HRI 2010, pp. 53–60 (2010). https://doi.org/10.1145/1734454.1734473

  40. Dragan, A.D., Lee, K.C.T., Srinivasa, S.S.: Legibility and predictability of robot motion. In: 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 301–308 (2013). https://doi.org/10.1109/HRI.2013.6483603

  41. Gannon, M.: Human-Centered Interfaces for Autonomous Fabrication Machines (2018)

    Google Scholar 

  42. LaViers, A.: Make robot motions natural. Nature 565, 422–424 (2019)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alicia Nahmad Vazquez .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Vazquez, A.N. (2022). Evaluating Team Fluency in Human-Industrial Robot Collaborative Design Tasks. In: Gerber, D., Pantazis, E., Bogosian, B., Nahmad, A., Miltiadis, C. (eds) Computer-Aided Architectural Design. Design Imperatives: The Future is Now. CAAD Futures 2021. Communications in Computer and Information Science, vol 1465. Springer, Singapore. https://doi.org/10.1007/978-981-19-1280-1_24

Download citation

  • DOI: https://doi.org/10.1007/978-981-19-1280-1_24

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1279-5

  • Online ISBN: 978-981-19-1280-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics