Advertisement

Journal of Bionic Engineering

, Volume 16, Issue 2, pp 209–221 | Cite as

Building a Plutchik’s Wheel Inspired Affective Model for Social Robots

  • Xianyu Qi
  • Wei WangEmail author
  • Lei Guo
  • Mingbo Li
  • Xiaoyu Zhang
  • Ran Wei
Article
  • 18 Downloads

Abstract

As more and more social robots are applied in human-populated environments, they need an affective model to communicate with human beings naturally and believably. In addition, the model should be flexible to be applied in different areas, such as entertainment and education, and can be easily understood and operated by robot designers. To meet these requirements, we propose an affective model including emotions, moods and personality traits for social robots to mimic the affect changes of human beings. Inspired by the Plutchik’s Wheel of Emotions, we first construct an affective space which can simultaneously represent the affective concepts. According to the affective space, the model can be visualized vividly and easily understood. We then describe the interaction among these concepts to change the robot states to make the robot interact with human beings naturally and believably. By tuning the parameters of the model, it can be flexibly applied in different areas. We evaluate the proposed model in simulation and human-robot interaction experiments and the experimental results show that the model is effective.

Keywords

human-robot interaction social robots affective model emotions moods personality traits 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgement

This work is supported by the National Natural Science Foundation of China (No. 91748101).

References

  1. [1]
    Leite I, Martinho C, Pereira A, Paiva A. As time goes by: Long-term evaluation of social presence in robotic companions. The 18th IEEE International Symposium on Robot and Human Interactive Communication, Toyama, Japan, 2009, 669–674.Google Scholar
  2. [2]
    Cavallo F, Aquilano M, Bonaccorsi M, Limosani R, Manzi A, Carrozza C M, Dario P. On the design, development and experimentation of the ASTRO assistive robot integrated in smart environments. IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 2013, 4310–4315.Google Scholar
  3. [3]
    Rane P, Mhatre V, Kurup L. Study of a home robot: Jibo. International Journal of Engineering Research and Technology, 2014, 3, 490–493.CrossRefGoogle Scholar
  4. [4]
    Reeves B, Nass C I. The Media Equation: How People Treat Computers, Television, and New Media like Real People and Places, Cambridge University Press, New York, USA, 1996, 3–18.Google Scholar
  5. [5]
    Cassell J, Sullivan J, Churchill E, Prevost S. Embodied Conversational Agents, MIT press, Cambridge, USA, 2000.CrossRefGoogle Scholar
  6. [6]
    Leite I, Martinho C, Paiva A. Social robots for long-term interaction: A survey. International Journal of Social Robotics, 2013, 5, 291–308.CrossRefGoogle Scholar
  7. [7]
    Scassellati B, Boccanfuso L, Huang C M, Mademtzi M, Qin M, Salomons N, Ventola P, Shic F. Improving social skills in children with ASD using a long-term, in-home social robot. Science Robotics, 2018, 3, eaat7544.CrossRefGoogle Scholar
  8. [8]
    Belpaeme T, Kennedy J, Ramachandran A, Scassellati B, Tanaka F. Social robots for education: A review. Science Robotics, 2018, 3, eaat5954.CrossRefGoogle Scholar
  9. [9]
    Cuadrado L E I, Riesco Á M, López F D L P. ARTIE: An integrated environment for the development of affective robot tutors. Frontiers in Computational Neuroscience, 2016, 10, 77–92.Google Scholar
  10. [10]
    Scherer K. The Neuropsychology of Emotion, Oxford University Press, Oxford, UK, 2000, 137–162.Google Scholar
  11. [11]
    Fong T, Nourbakhsh I, Dautenhahn K. A survey of socially interactive robots. Robotics and Autonomous Systems, 2003, 42, 143–166.CrossRefzbMATHGoogle Scholar
  12. [12]
    Ekman P, Friesen W V. Constants across cultures in the face and emotion. Journal of Personality and Social Psychology, 1971, 17, 124–129.CrossRefGoogle Scholar
  13. [13]
    Russell J A. A circumplex model of affect. Journal of Personality and Social Psychology, 1980, 39, 1161–1178.CrossRefGoogle Scholar
  14. [14]
    Robert P. Emotion: A Psychoevolutionary Synthesis, Harpercollins College Division, New York, USA, 1980.Google Scholar
  15. [15]
    Hume D. Organizational Behavior, Prentice Hall, New Jersey, USA, 2012, 258–297.Google Scholar
  16. [16]
    Neumann R, Seibt B, Strack F. The influence of mood on the intensity of emotional responses: Disentangling feeling and knowing. Cognition and Emotion, 2001, 15, 725–747.CrossRefGoogle Scholar
  17. [17]
    McCrae R R, John O P. An introduction to the five-factor model and its applications. Journal of Personality, 1992, 60, 175–215.CrossRefGoogle Scholar
  18. [18]
    Rodríguez L F, Ramos F. Development of computational models of emotions for autonomous agents: A review. Cognitive Computation, 2014, 6, 351–375.CrossRefGoogle Scholar
  19. [19]
    Calvo R A, D’Mello S, Gratch J, Kappas A. The Oxford Handbook of Affective Computing, Oxford Library of Psychology, Oxford, UK, 2015.CrossRefGoogle Scholar
  20. [20]
    Höök K. Affective loop experiences: Designing for interactional embodiment. Philosophical Transactions of the Royal Society B: Biological Sciences, 2009, 364, 3585–3595.CrossRefGoogle Scholar
  21. [21]
    Breazeal C L. Designing Sociable Robots, MIT press, Cambridge, USA, 2004.CrossRefzbMATHGoogle Scholar
  22. [22]
    Han J, Xie L, Li D, He Z J, Wang Z L. Cognitive emotion model for eldercare robot in smart home. China Communications, 2015, 12, 32–41.Google Scholar
  23. [23]
    Saldien J, Goris K, Vanderborght B, Vanderfaeillie J, Lefeber D. Expressing emotions with the social robot probo. International Journal of Social Robotics, 2010, 2, 377–389.CrossRefGoogle Scholar
  24. [24]
    Cao H L, Esteban P G, Albert D B, Simut R, Van de Perre G, Lefeber D, Vanderborght B. A collaborative homeostaticbased behavior controller for social robots in human-robot interaction experiments. International Journal of Social Robotics, 2017, 9, 675–690.CrossRefGoogle Scholar
  25. [25]
    Alvarez M, Galan R, Matia F, Rodriguez-Losada D, Jimenez A. An emotional model for a guide robot. IEEE Transactions on Systems, Man, and Cybernetics — Part A: Systems and Humans, 2010, 40, 982–992.CrossRefGoogle Scholar
  26. [26]
    Malfaz M, Castro-González Á, Barber R, Salichs M A. A biologically inspired architecture for an autonomous and social robot. IEEE Transactions on Autonomous Mental Development, 2011, 3, 232–246.CrossRefGoogle Scholar
  27. [27]
    Wang Y, Wang Z L, Wang W. Research on associative memory models of emotional robots. Advances in Mechanical Engineering, 2014, 6, 208153.CrossRefGoogle Scholar
  28. [28]
    Kirby R, Forlizzi J, Simmons R. Affective social robots. Robotics and Autonomous Systems, 2010, 58, 322–332.CrossRefGoogle Scholar
  29. [29]
    Miwa H, Okuchi T, Itoh K, Takanobu H, Takanishi A. A new mental model for humanoid robots for human friendly communication introduction of learning system, mood vector and second order equations of emotion. IEEE International Conference on Robotics and Automation, Taipei, China, 2003, 3588–3593.Google Scholar
  30. [30]
    Long L N. A model for temperament and emotions on robots. The 8th International Conference on Applied Human Factors and Ergonomics, Los Angeles, USA, 2017, 3–13.Google Scholar
  31. [31]
    Gebhard P. ALMA: A layered model of affect. Proceedings of the 4th International Joint Conference on Autonomous Agents and Multiagent Systems, New York, USA, 2005, 29–36.Google Scholar
  32. [32]
    Han M J, Lin C H, Song K T. Robotic emotional expression generation based on mood transition and personality model. IEEE Transactions on Cybernetics, 2013, 43, 1290–1303.CrossRefGoogle Scholar
  33. [33]
    Masuyama N, Loo C K, Seera M. Personality affected robotic emotional model with associative memory for human-robot interaction. Neurocomputing, 2018, 272, 213–225.CrossRefGoogle Scholar
  34. [34]
    Cavallo F, Semeraro F, Fiorini L, Magyar G, Sinčák P, Dario P. Emotion modelling for social robotics applications: A review. Journal of Bionic Engineering, 2018, 15, 185–203.CrossRefGoogle Scholar
  35. [35]
    Gerrig R J, Zimbardo P G, Campbell A J, Cumming S R, Wilkes F J. Psychology and Life, Pearson Higher Education, Melbourne, Australia, 2015.Google Scholar
  36. [36]
    Steephen J E. HED: A computational model of affective adaptation and emotion dynamics. IEEE Transactions on Affective Computing, 2013, 4, 197–210.CrossRefGoogle Scholar
  37. [37]
    Wilson T D, Gilbert D T. Explaining away: A model of affective adaptation. Perspectives on Psychological Science, 2008, 3, 370–386.CrossRefGoogle Scholar
  38. [38]
    Lyubomirsky S. Hedonic adaptation to positive and negative experiences. The Oxford Handbook of Stress, Health, and Coping, Oxford University Press, Oxford, UK, 2012.Google Scholar
  39. [39]
    Katsimerou C, Heynderickx I, Redi J A. Predicting mood from punctual emotion annotations on videos. IEEE Transactions on Affective Computing, 2015, 6, 179–192.CrossRefGoogle Scholar
  40. [40]
    Lucas R E, Clark A E, Georgellis Y, Diener E. Reexamining adaptation and the set point model of happiness: Reactions to changes in marital status. Journal of Personality and Social Psychology, 2003, 84, 527–539.CrossRefGoogle Scholar
  41. [41]
    Diener E, Lucas R E, Scollon C N. The Science of Well-Being, Springer, Dordrecht, Netherlands, 2009, 103–118.Google Scholar
  42. [42]
    Lund A M. Measuring usability with the USE questionnaire. Usability Interface, 2001, 8, 3–6.Google Scholar

Copyright information

© Jilin University 2019

Authors and Affiliations

  • Xianyu Qi
    • 1
  • Wei Wang
    • 1
    Email author
  • Lei Guo
    • 2
  • Mingbo Li
    • 2
  • Xiaoyu Zhang
    • 1
  • Ran Wei
    • 2
  1. 1.Robotics InstituteBeihang UniversityBeijingChina
  2. 2.Beijing Evolver Robotics Technology Co., LtdBeijingChina

Personalised recommendations