1887
  1. Home
  2. e-Journals
  3. Interaction Studies
  4. Volume 23, Issue 3
  5. Article
Volume 23, Issue 3
  • ISSN 1572-0373
  • E-ISSN: 1572-0381
USD
Buy:$35.00 + Taxes

Abstract

Abstract

A key factor for the acceptance of robots as regular partners in human-centered environments is the appropriateness and predictability of their behaviors, which depend partially on the robot behavior’s conformity to social norms. Previous experimental studies have shown that robots that follow social norms and the corresponding interactions are perceived more positively by humans than robots or interactions that do not adhere to social norms. However, the conducted studies only focused on the effects of social norm compliance in specific scenarios. Therefore, this paper aims to guide further research studies by compiling how researchers in relevant research fields think the perception of robots and the corresponding interactions are influenced independently of a specific scenario if a robot’s behavior conforms to social norms. Additionally, this study investigates what characteristics and metrics constitute a good general benchmark to objectively evaluate the behavior of social robots regarding its conformity to social norms according to researchers in relevant research communities. Finally, the paper summarizes how the obtained results can guide future research toward socially aware robot behavior.

© 2022 John Benjamins Publishing Company
Loading

Article metrics loading...

/content/journals/10.1075/is.22029.roe
2023-04-21
2024-12-14

  • From This Site

    /content/journals/10.1075/is.22029.roe
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Cabin, R. J., & Mitchell, R. J.
    (2000) To Bonferroni or not to Bonferroni: when and how are the questions. Bulletin of the ecological society of America, 81(3), 246–248.
     [Google Scholar]
  2. Ciou, P.-H., Hsiao, Y.-T., Wu, Z.-Z., Tseng, S.-H., & Fu, L.-C.
    (2018) Composite reinforcement learning for social robot navigation. InProceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (p.2553–2558). 10.1109/IROS.2018.8593410
     https://doi.org/10.1109/IROS.2018.8593410 [Google Scholar]
  3. Dautenhahn, K., Walters, M., Woods, S., Koay, K. L., Nehaniv, C. L., Sisbot, A., … Simeon, T.
    (2006) How may I serve you? A robot companion approaching a seated person in a helping context. InProceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction (p.172–179). 10.1145/1121241.1121272
     https://doi.org/10.1145/1121241.1121272 [Google Scholar]
  4. Gao, Y., Yang, F., Frisk, M., Hemandez, D., Peters, C., & Castellano, G.
    (2019) Learning socially appropriate robot approaching behavior toward groups using deep reinforcement learning. InProceedings of the 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN) (p.1–8). 10.1109/RO‑MAN46459.2019.8956444
     https://doi.org/10.1109/RO-MAN46459.2019.8956444 [Google Scholar]
  5. Joosse, M., Lohse, M., & Evers, V.
    (2014) Lost in proxemics: spatial behavior for cross-cultural HRI. InProceedings of the HRI 2014 Workshop on Culture-Aware Robotics (p.1–6).
     [Google Scholar]
  6. Koay, K. L., Syrdal, D. S., Walters, M. L., & Dautenhahn, K.
    (2007) Living with robots: Investigating the habituation effect in participants’ preferences during a longitudinal human-robot interaction study. InProceedings of the 16th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN) (p.564–569).
     [Google Scholar]
  7. Kruse, T., Pandey, A., Alami, R., & Kirsch, A.
    (2013, December). Human-Aware Robot Navigation: A Survey. Robotics and Autonomous Systems, 61(12), 1726–1743. 10.1016/j.robot.2013.05.007
     https://doi.org/10.1016/j.robot.2013.05.007 [Google Scholar]
  8. Li, D., Rau, P.-L., & Li, Y.
    (2010) A cross-cultural study: Effect of robot appearance and task. International Journal of Social Robotics, 2(2), 175–186. 10.1007/s12369‑010‑0056‑9
     https://doi.org/10.1007/s12369-010-0056-9 [Google Scholar]
  9. Mensah, Y. M., & Chen, H.-Y.
    (2013, April). Global Clustering of Countries by Culture – An Extension of the GLOBE Study. SSRN.
     [Google Scholar]
  10. Nakagawa, S.
    (2004) A farewell to Bonferroni: the problems of low statistical power and publication bias. Behavioral ecology, 15(6), 1044–1045. 10.1093/beheco/arh107
     https://doi.org/10.1093/beheco/arh107 [Google Scholar]
  11. Perneger, T. V.
    (1998) What’s wrong with Bonferroni adjustments. BMJ, 316(7139), 1236–1238. 10.1136/bmj.316.7139.1236
     https://doi.org/10.1136/bmj.316.7139.1236 [Google Scholar]
  12. Sarathy, V., Wilson, J. R., Arnold, T., & Scheutz, M.
    (2016) Enabling basic normative HRI in a cognitive robotic architecture. arXiv preprint arXiv:1602.03814.
     [Google Scholar]
  13. Takayama, L., & Pantofaru, C.
    (2009) Influences on proxemic behaviors in human-robot interaction. InProceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (p.5495–5502). 10.1109/IROS.2009.5354145
     https://doi.org/10.1109/IROS.2009.5354145 [Google Scholar]
  14. Tomic, S., Pecora, F., & Saffiotti, A.
    (2014, August). Too Cool for School – Adding Social Constraints inHuman Aware Planning. InThe 9th International Workshop on Cognitive Robotics (CogRob). Prague, Czech Republic.
     [Google Scholar]
  15. Trovato, G., Zecca, M., Sessa, S., Jamone, L., Ham, J., Hashimoto, K., & Takanishi, A.
    (2013) Cross-cultural study on human-robot greeting interaction: acceptance and discomfort by Egyptians and Japanese. Paladyn, Journal of Behavioral Robotics, 4(2), 83–93. 10.2478/pjbr‑2013‑0006
     https://doi.org/10.2478/pjbr-2013-0006 [Google Scholar]
  16. Wang, L., Rau, P.-L. P., Evers, V., Robinson, B. K., & Hinds, P.
    (2010) When in Rome: the role of culture & context in adherence to robot recommendations. InProceedings of the 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (p.359–366). 10.1145/1734454.1734578
     https://doi.org/10.1145/1734454.1734578 [Google Scholar]
/content/journals/10.1075/is.22029.roe
Loading
Toward understanding the effects of socially aware robot behavior
Interaction Studies 23, 513 (2022); https://doi.org/10.1075/is.22029.roe
/content/journals/10.1075/is.22029.roe
/content/journals/10.1075/is.22029.roe
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): benchmarks; metrics; robot behavior adaptation; social norms; socially aware robot behavior

Most Cited

This is a required field
Please enter a valid email address
Approval was successful
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error