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JACIII Vol.29 No.6 pp. 1530-1540
doi: 10.20965/jaciii.2025.p1530
(2025)

Research Paper:

Does Robot Clothing Really Help? User Preferences and Effects in Simulated Domestic Scenarios

Kazunari Yoshiwara* ORCID Icon and Kazuki Kobayashi** ORCID Icon

*Research Center for Social Systems, Shinshu University
4-17-1 Wakasato, Nagano, Nagano 380-8553, Japan

**Academic Assembly, Shinshu University
4-17-1 Wakasato, Nagano, Nagano 380-8553, Japan

Received:
April 23, 2025
Accepted:
August 6, 2025
Published:
November 20, 2025
Keywords:
clothing for robots, human–robot interaction, robot’s appearance
Abstract

This study investigated the impact of clothing on robot appearance, particularly in scenarios where a single robot performs multiple tasks. Clothing depicts an individual’s role and capability toward others. Applying this effect to robot appearance design can enable an individual robot to express roles and capabilities suitable for multiple tasks. This makes it a potentially effective approach to robot appearance design. Our experiments first investigated the user acceptance of robots wearing clothing. Subsequently, we investigated the impact of robot attire on user behavior and impressions in a shared workspace. Our results indicate that users prefer robots to wear clothing only during cooking. In addition, in scenarios wherein robots and users share a workspace while performing different tasks, robot clothing is associated with negative user impressions. These observations indicate that even when users express a preference for clothed robots, the actual effect may not be positive and can vary depending on the task and context of use. Therefore, the decision to clothe a robot requires cautious consideration.

Robot housekeeping tasks within the experiment

Robot housekeeping tasks within the experiment

Cite this article as:
K. Yoshiwara and K. Kobayashi, “Does Robot Clothing Really Help? User Preferences and Effects in Simulated Domestic Scenarios,” J. Adv. Comput. Intell. Intell. Inform., Vol.29 No.6, pp. 1530-1540, 2025.
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References
  1. [1] T. Belpaeme, J. Kennedy, A. Ramachandran, B. Scassellati, and F. Tanaka, “Social robots for education: A review,” Science Robotics, Vol.3, No.21, Article No.eaat5954, 2018. https://doi.org/10.1126/scirobotics.aat5954
  2. [2] C. Huisman and H. Kort, “Two-year use of care robot Zora in Dutch nursing homes: An evaluation study,” Healthcare, Vol.7, No.1, Article No.31, 2019. https://doi.org/10.3390/healthcare7010031
  3. [3] H. Hejazipoor, J. Massah, M. Soryani, K. A. Vakilian, and G. Chegini, “An intelligent spraying robot based on plant bulk volume,” Computers and Electronics in Agriculture, Vol.180, Article No.105859, 2021. https://doi.org/10.1016/j.compag.2020.105859
  4. [4] M. Heerink, B. Vanderborght, J. Broekens, and J. Albó-Canals, “New friends: Social robots in therapy and education,” Int. J. of Social Robotics, Vol.8, No.4, pp. 443-444, 2016. https://doi.org/10.1007/s12369-016-0374-7
  5. [5] M. L. Walters, D. S. Syrdal, K. L. Koay, K. Dautenhahn, and R. te Boekhorst, “Human approach distances to a mechanical-looking robot with different robot voice styles,” 17th IEEE Int. Symp. on Robot and Human Interactive Communication (RO-MAN 2008), pp. 707-712, 2008. https://doi.org/10.1109/ROMAN.2008.4600750
  6. [6] K. Nakagawa et al., “Effect of robot’s whispering behavior on people’s motivation,” Int. J. of Social Robotics, Vol.5, No.1, pp. 5-16, 2013. https://doi.org/10.1007/s12369-012-0141-3
  7. [7] P. H. Kahn, Jr. et al., “Will people keep the secret of a humanoid robot?: Psychological intimacy in HRI,” Proc. of the 10th Annual ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI’15), pp. 173-180, 2015. https://doi.org/10.1145/2696454.2696486
  8. [8] M. Lohse, F. Hegel, and B. Wrede, “Domestic applications for social robots: An online survey on the influence of appearance and capabilities,” J. of Physical Agents, Vol.2, No.2, pp. 21-32, 2008. https://doi.org/10.14198/JoPha.2008.2.2.04
  9. [9] K. S. Haring, K. Watanabe, M. Velonaki, C. C. Tossell, and V. Finomore, “FFAB—The form function attribution bias in human–robot interaction,” IEEE Trans. on Cognitive and Developmental Systems, Vol.10, No.4, pp. 843-851, 2018. https://doi.org/10.1109/TCDS.2018.2851569
  10. [10] M. Paetzel, G. Perugia, and G. Castellano, “The persistence of first impressions: The effect of repeated interactions on the perception of a social robot,” Proc. of the 2020 ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI’20), pp. 73-82, 2020. https://doi.org/10.1145/3319502.3374786
  11. [11] G. Perugia et al., “Models of (often) ambivalent robot stereotypes: Content, structure, and predictors of robots’ age and gender stereotypes,” Proc. of the 2023 ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI’23), pp. 428-436, 2023. https://doi.org/10.1145/3568162.3576981
  12. [12] S. Song and S. Yamada, “Designing LED lights for communicating gaze with appearance-constrained robots,” 27th IEEE Int. Symp. on Robot and Human Interactive Communication (RO-MAN), pp. 94-97, 2018. https://doi.org/10.1109/ROMAN.2018.8525661
  13. [13] T. Inamura, “Digital twin of experience for human–robot collaboration through virtual reality,” Int. J. Automation Technol., Vol.17, No.3, pp. 284-291, 2023. https://doi.org/10.20965/ijat.2023.p0284
  14. [14] B. Brogi et al., “The Avatarm: Interacting in the physical metaverse via robotics, diminished reality, and haptics,” IEEE Access, Vol.12, pp. 90750-90767, 2024. https://doi.org/10.1109/ACCESS.2024.3420717
  15. [15] R. Suzuki, A. Karim, T. Xia, H. Hedayati, and N. Marquardt, “Augmented reality and robotics: A survey and taxonomy for AR-enhanced human-robot interaction and robotic interfaces,” Proc. of the 2022 CHI Conf. on Human Factors in Computing Systems (CHI’22), Article No.553, 2022. https://doi.org/10.1145/3491102.3517719
  16. [16] C. T. Chang and B. Hayes, “A survey of augmented reality for human–robot collaboration,” Machines, Vol.12, No.8, Article No.540, 2024. https://doi.org/10.3390/machines12080540
  17. [17] C. Liu and L. Xie, “Formal versus casual: How do customers respond to service robots’ uniforms? The roles of service type and language style,” Int. J. of Hospitality Management, Vol.114, Article No.103566, 2023. https://doi.org/10.1016/j.ijhm.2023.103566
  18. [18] Y. Cheng and Y. Wang, “Evaluating the effect of outfit on personality perception in virtual characters,” Virtual Worlds, Vol.3, No.1, pp. 21-39, 2024. https://doi.org/10.3390/virtualworlds3010002
  19. [19] K. V. Hindriks, M. Hagenaar, and A. L. Huckelba, “Effects of robot clothing on first impressions, gender, human-likeness, and suitability of a robot for occupations,” 31st IEEE Int. Conf. on Robot and Human Interactive Communication (RO-MAN), pp. 428-435, 2022. https://doi.org/10.1109/RO-MAN53752.2022.9900771
  20. [20] J. Hurtienne and D. Arnold, “The naked truth?” Companion of the 2020 ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI’20), pp. 269-271, 2020. https://doi.org/10.1145/3371382.3378362
  21. [21] T. Sugiyama and M. Kanoh, “Investigating emotional impressions in robots using clothing colors,” J. Adv. Comput. Intell. Intell. Inform., Vol.28, No.1, pp. 79-85, 2024. https://doi.org/10.20965/jaciii.2024.p0079
  22. [22] K. Yoshiwara and K. Kobayashi, “Effect on user impression of robot’s task dependent uniform,” Proc. of the 5th Int. Conf. on Computer-Human Interaction Research and Applications (CHIRA), Vol.1, pp. 90-97, 2021. https://doi.org/10.5220/0010684500003060
  23. [23] K. Yoshiwara and K. Kobayashi, “The effect on user impression of household robots’ clothing changes,” J. of Japan Society for Fuzzy Theory and Intelligent Informatics, Vol.35, No.4, pp. 769-779, 2023 (in Japanese). https://doi.org/10.3156/jsoft.35.4_769
  24. [24] G. Havenith, “Interaction of clothing and thermoregulation,” Exogenous Dermatology, Vol.1, No.5, pp. 221-230, 2002. https://doi.org/10.1159/000068802
  25. [25] N. Joseph and N. Alex, “The uniform: A sociological perspective,” American J. of Sociology, Vol.77, No.4, pp. 719-730, 1972. https://doi.org/10.1086/225197
  26. [26] M. S. Singer and A. E. Singer, “The effect of police uniform on interpersonal perception.” The J. of Psychology, Vol.119, No.2, pp. 157-161, 1985. https://doi.org/10.1080/00223980.1985.10542882
  27. [27] R. A. R. Gurung, L. Kempen, K. Klemm, R. Senn, and R. Wysocki, “Dressed to present: Ratings of classroom presentations vary with attire,” Teaching of Psychology, Vol.41, No.4, pp. 349-353, 2014. https://doi.org/10.1177/0098628314549710
  28. [28] C. Y. Shao, J. A. Baker, and J. Wagner, “The effects of appropriateness of service contact personnel dress on customer expectations of service quality and purchase intention: The moderating influences of involvement and gender,” J. of Business Research, Vol.57, No.10, pp. 1164-1176, 2004. https://doi.org/10.1016/S0148-2963(02)00326-0
  29. [29] N. Friedman et al., “What robots need from clothing,” Proc. of the 2021 ACM Designing Interactive Systems Conf. (DIS’21), pp. 1345-1355, 2021. https://doi.org/10.1145/3461778.3462045
  30. [30] N. Friedman et al., “Designing functional clothing for human-robot interaction,” Companion of the 2021 ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI’21), pp. 703-705, 2021. https://doi.org/10.1145/3434074.3444870
  31. [31] G. Bugmann and S. N. Copleston, “What can a personal robot do for you?,” Proc. of the 12th Annual Conf. on Towards Autonomous Robotic Systems (TAROS 2011), pp. 360-371, 2011. https://doi.org/10.1007/978-3-642-23232-9_32
  32. [32] D. Kang, S. S. Kwak, H. Lee, and J. Choi, “First things first: A survey exploring key services and functions of a robot,” Companion of the 2020 ACM/IEEE Int. Conf. on Human-Robot Interaction (HRI’20), pp. 278-280, 2020. https://doi.org/10.1145/3371382.3378317
  33. [33] A. K. Pandey and R. Gelin, “A mass-produced sociable humanoid robot: Pepper: The first machine of its kind,” IEEE Robotics & Automation Magazine, Vol.25, No.3, pp. 40-48, 2018. https://doi.org/10.1109/MRA.2018.2833157
  34. [34] E. Schneiders, A. M. Kanstrup, J. Kjeldskov, and M. B. Skov, “Domestic robots and the dream of automation: Understanding human interaction and intervention,” Proc. of the 2021 CHI Conf. on Human Factors in Computing Systems (CHI’21), Article No.241, 2021. https://doi.org/10.1145/3411764.3445629
  35. [35] S. Fitrianie, M. Bruijnes, D. Richards, A. Bönsch, and W.-P. Brinkman, “The 19 unifying questionnaire constructs of artificial social agents: An IVA community analysis,” Proc. of the 20th ACM Int. Conf. on Intelligent Virtual Agents (IVA’20), Article No.21, 2020. https://doi.org/10.1145/3383652.3423873
  36. [36] T. Hoßfeld et al., “Quantification of YouTube QoE via crowdsourcing,” 2011 IEEE Int. Symp. on Multimedia, pp. 494-499, 2011. https://doi.org/10.1109/ISM.2011.87
  37. [37] N. Castelo and M. Sarvary, “Cross-cultural differences in comfort with humanlike robots,” Int. J. of Social Robotics, Vol.14, No.8, pp. 1865-1873, 2022. https://doi.org/10.1007/s12369-022-00920-y
  38. [38] H. Kamide et al., “A comparative psychological evaluation of a robotic avatar in Dubai and Japan,” Frontiers in Robotics and AI, Vol.11, Article No.1426717, 2025. https://doi.org/10.3389/frobt.2024.1426717

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Last updated on Nov. 19, 2025