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Active Participatory Social Robot Design Using Mind Perception Attributes

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Social Robotics (ICSR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13818))

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Abstract

The Build-A-Bot online platform has been developed with the goal to enable active participatory design and broaden the participation in social robot design. The platform is hosted on a webpage to make robot design widely available. Active participatory design is enabled by giving the user the maximum amount of creative freedom in creating their own designs. The platform uses a form of gamification that challenges the user to build robot designs that emulate an experience or agency capability. The overall goal is to create a comprehensive set of robot designs that are related to such an attribute. This data then will allow us to research robot mind perception using Machine Learning and neuroscience methods in the future. This work focuses on the development of the online Build-A-Bot platform and the methodology implemented on the platform.

This research has been sponsored by the University of Denver under the Professional Research Opportunities for Faculty (PROF) opportunity to Drs. Haring, Kim, and Pittman under grant \(\#\) 142101-84994 and by the University of Denver under the Faculty Research Funds (FRF) to Drs. Haring and Pittman under grant \(\#\) 142101-84694.

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References

  1. Angular. https://angular.io/

  2. MongoDB: The Developer Data Platform. https://www.mongodb.com

  3. Neo4j Graph Data Platform - The Leader in Graph Databases. https://neo4j.com/

  4. van den Berghe, R., Verhagen, J., Oudgenoeg-Paz, O., Van der Ven, S., Leseman, P.: Social robots for language learning: A review. Rev. Educ. Res. 89(2), 259–295 (2019)

    Article  Google Scholar 

  5. Carpenter, J.: The Quiet Professional: An investigation of US military Explosive Ordnance Disposal personnel interactions with everyday field robots. Ph.D. thesis (2013)

    Google Scholar 

  6. Cha, E., Dragan, A.D., Srinivasa, S.S.: Perceived robot capability. In: 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), pp. 541–548. IEEE (2015)

    Google Scholar 

  7. Corrigan, L.J., Basedow, C., Kïster, D., Kappas, A., Peters, C., Castellano, G.: Mixing implicit and explicit probes: finding a ground truth for engagement in social human-robot interactions. In: 2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI), pp. 140–141. IEEE (2014)

    Google Scholar 

  8. Dino, F., Zandie, R., Abdollahi, H., Schoeder, S., Mahoor, M.H.: Delivering cognitive behavioral therapy using a conversational social robot. In: 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2089–2095. IEEE (2019)

    Google Scholar 

  9. Figma (2021). https://www.figma.com/ (25 Aug 2021)

  10. Forlizzi, J., DiSalvo, C.: Service robots in the domestic environment: a study of the roomba vacuum in the home. In: Proceedings of the 1st ACM SIGCHI/SIGART onference on Human-Robot Interaction, pp. 258–265 (2006)

    Google Scholar 

  11. Gray, H.M., Gray, K., Wegner, D.M.: Dimensions of mind perception. Science 315(5812), 619–619 (2007)

    Article  Google Scholar 

  12. Haring, K.S., Phillips, E., Lazzara, E.H., Ullman, D., Baker, A.L., Keebler, J.R.: Applying the swift trust model to human-robot teaming. In: Trust in Human-Robot Interaction, pp. 407–427. Elsevier (2021)

    Google Scholar 

  13. Haring, K.S., Watanabe, K., Velonaki, M., Tossell, C.C., Finomore, V.: FFAB-The form function attribution bias in human-robot interaction. IEEE Trans. Cogn. Developm. Syst. 10(4), 843–851 (2018)

    Article  Google Scholar 

  14. Henry, S.L., Abou-Zahra, S., Brewer, J.: The role of accessibility in a universal web. In: Proceedings of the 11th Web for all Conference, pp. 1–4 (2014)

    Google Scholar 

  15. Himichi, T., Nomura, M.: Modulation of empathy in the left ventrolateral prefrontal cortex facilitates altruistic behavior: An fNIRS study. J. Integr. Neurosci. 14(02), 207–222 (2015)

    Article  Google Scholar 

  16. Huang, L., Gillan, D.: An exploration of robot builders’ emotional responses to their tournament robots. In: Proceedings of the Human Factors And Ergonomics Society Annual Meeting, vol. 58, pp. 2013–2017. SAGE Publications Sage CA: Los Angeles, CA (2014)

    Google Scholar 

  17. Huang, L., Varnado, T., Gillan, D.: An exploration of robot builders’ attachment to their lego robots. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 57, pp. 1825–1829. SAGE Publications Sage CA: Los Angeles, CA (2013)

    Google Scholar 

  18. Keller, L., John, I.: How can computer science faculties increase the proportion of women in computer science by using robots? In: 2019 IEEE Global Engineering Education Conference (EDUCON), pp. 206–210. IEEE (2019)

    Google Scholar 

  19. Kumar, A.: Integrating with Blender, Maya and Marmoset. In: Beginning PBR Texturing, pp. 165–186. Apress, Berkeley, CA (2020). https://doi.org/10.1007/978-1-4842-5899-6_16

    Chapter  Google Scholar 

  20. Küster, D., Swiderska, A.: Seeing the mind of robots: Harm augments mind perception but benevolent intentions reduce dehumanisation of artificial entities in visual vignettes. Int. J. Psychol. 56(3), 454–465 (2021)

    Article  Google Scholar 

  21. Lochner, D.: Creature Creator (2021). https://github.com/daniellochner/Creature-Creator

  22. Matthews, G., Lin, J., Panganiban, A.R., Long, M.D.: Individual differences in trust in autonomous robots: Implications for transparency. IEEE Trans. Hum. Mach. Syst. 50(3), 234–244 (2019)

    Article  Google Scholar 

  23. Muller, M.J.: Participatory design: the third space in HCI. CRC Press (2007)

    Google Scholar 

  24. Norman, D.A.: Emotional design: Why we love (or hate) everyday things. Civitas Books (2004)

    Google Scholar 

  25. Peerdeman, P.: Sound and music in games. Amsterdam: VrijeUniversiteit, pp. 2–3 (2010)

    Google Scholar 

  26. Phillips, E., Ullman, D., de Graaf, M.M., Malle, B.F.: What does a robot look like?: A multi-site examination of user expectations about robot appearance. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 61, pp. 1215–1219. SAGE Publications Sage CA: Los Angeles, CA (2017)

    Google Scholar 

  27. Phillips, E., Zhao, X., Ullman, D., Malle, B.F.: What is human-like? Decomposing robots’ human-like appearance using the anthropomorphic robot (ABOT) database. In: Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction, pp. 105–113 (2018)

    Google Scholar 

  28. Plaza, P., et al.: Educational robotics for all: Gender, diversity, and inclusion in steam. In: 2020 IEEE Learning With MOOCS (LWMOOCS), pp. 19–24. IEEE (2020)

    Google Scholar 

  29. Ramírez-Duque, A.A., et al.: Collaborative and inclusive process with the autism community: a case study in colombia about social robot design. Int. J. Soc. Robot. 13(2), 153–167 (2020). https://doi.org/10.1007/s12369-020-00627-y

    Article  Google Scholar 

  30. Raposo, D., Santoro, A., Barrett, D., Pascanu, R., Lillicrap, T., Battaglia, P.: Discovering objects and their relations from entangled scene representations. arXiv preprint arXiv:1702.05068 (2017)

  31. Ritter, S.M., Ferguson, S.: Happy creativity: Listening to happy music facilitates divergent thinking. PLoS ONE 12(9), e0182210 (2017)

    Article  Google Scholar 

  32. Robertson, T., Simonsen, J.: Challenges and opportunities in contemporary participatory design. Des. Issues 28(3), 3–9 (2012)

    Article  Google Scholar 

  33. Sampietro, A.: Use and interpretation of emoji in electronic-mediated communication: A survey. Vis. Commun. Q. 27(1), 27–39 (2020)

    Article  Google Scholar 

  34. Schaefer, K.E., Sanders, T.L., Yordon, R.E., Billings, D.R., Hancock, P.A.: Classification of robot form: Factors predicting perceived trustworthiness. In: Proceedings of the Human Factors And Ergonomics Society Annual Meeting, vol. 56, pp. 1548–1552. SAGE Publications Sage CA: Los Angeles, CA (2012)

    Google Scholar 

  35. Scherer, R., Siddiq, F., Tondeur, J.: The technology acceptance model (tam): A meta-analytic structural equation modeling approach to explaining teachers’ adoption of digital technology in education. Comput. Educ. 128, 13–35 (2019)

    Article  Google Scholar 

  36. Schramm, L.T., Dufault, D., Young, J.E.: Warning: This robot is not what it seems! exploring expectation discrepancy resulting from robot design. In: Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, pp. 439–441 (2020)

    Google Scholar 

  37. Senkic, D.: Dynamic simulation in a 3d-environment: A comparison between maya and blender (2010)

    Google Scholar 

  38. Smith, M.B.: 3d character modeling in maya and blender. Undergraduate Honors Theses 120 (2017). https://thekeep.eiu.edu/honors_theses/120

  39. Store, U.A.: Unity multipurpose avatar (2022). https://assetstore.unity.com/packages/3d/characters/uma-2-unity-multipurpose-avatar-35611. (Accessed 16 August 2022)

  40. Technologies U: Unity - Manual: Building your WebGL application. https://docs.unity3d.com/Manual/webgl-building.html

  41. Technologies U: Unity Real-Time Development Platform — 3D, 2D VR & AR Engine. https://unity.com/

  42. Thellman, S., de Graaf, M., Ziemke, T.: Mental state attribution to robots: A systematic review of conceptions, methods, and findings. ACM Trans. Hum. Robot Interact. (2021)

    Google Scholar 

  43. Totten, C.: Game character creation with blender and unity. John Wiley & Sons (2012)

    Google Scholar 

  44. Zichermann, G., Cunningham, C.: Gamification by design: Implementing game mechanics in web and mobile apps. O’Reilly Media, Inc. (2011)

    Google Scholar 

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Acknowledgment

We are grateful to our students Abdul Ayad, Mike Blanding, Marley Bogran, Madeline Bohn, William Bohrmann, Gillian Ehman, Josh Ellis, Angel Fernandes, Tanner Francis, Sergio Gonzales, Elizabeth Gutierrez-Gutierrez, Ulises A. Heredia Trinidad, Beatriz Hernandez, Esabella Irby, Henry Jaffray, Izzy Johnson, Braden Kelsey, Yahir Luevano-Estrada, Nicholas Ninos, Sneha Patil, Max Peterson, Yasmin Raz, Hector Armando Rodriguez, Ashley Sanchez, Grace Strasheim, Raghav Thapa, Maisey Toczek, and Ralph Vrooman for their work on DU Build-A-Bot.

Author information

Authors and Affiliations

  1. Build–A–Bot Laboratory, Ritchie School of Engineering and Computer Science, University of Denver, Denver, CO, USA

    Weston Laity, Benjamin Dossett, Robel Mamo, Daniel Pittman & Kerstin Haring

  2. Metropolitan State University, Denver, CO, USA

    Daniel Pittman

Authors
  1. Weston Laity
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  2. Benjamin Dossett
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  3. Robel Mamo
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  4. Daniel Pittman
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  5. Kerstin Haring
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Corresponding author

Correspondence to Kerstin Haring .

Editor information

Editors and Affiliations

  1. University of Florence, Florence, Italy

    Filippo Cavallo

  2. Qatar University, Doha, Qatar

    John-John Cabibihan

  3. University of Florence, Florence, Italy

    Laura Fiorini

  4. University of Florence, Florence, Italy

    Alessandra Sorrentino

  5. Wichita State University, Wichita, KS, USA

    Hongsheng He

  6. Qingdao University, Qingdao, China

    Xiaorui Liu

  7. National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan

    Yoshio Matsumoto

  8. National University of Singapore, Singapore, Singapore

    Shuzhi Sam Ge

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Laity, W., Dossett, B., Mamo, R., Pittman, D., Haring, K. (2022). Active Participatory Social Robot Design Using Mind Perception Attributes. In: Cavallo, F., et al. Social Robotics. ICSR 2022. Lecture Notes in Computer Science(), vol 13818. Springer, Cham. https://doi.org/10.1007/978-3-031-24670-8_50

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  • DOI: https://doi.org/10.1007/978-3-031-24670-8_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-24669-2

  • Online ISBN: 978-3-031-24670-8

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