Embodiment, Situatedness, and Morphology for Humanoid Robots Interacting with People

  • Blanca Miller
  • David Feil-SeiferEmail author
Reference work entry


The aim of human-robot interaction (HRI) is that people intuitively understand robots. When integrating humanoid robots into our daily lives, a myriad of factors can influence how a person perceives and interacts with a robot. Particularly, humanoid robots’ embodiment, situatedness, and morphology can individually and collectively affect the interactions between a person and robot, including the utilitarian and aesthetic factors of the robot’s physical design. It is therefore necessary to investigate how humanoid design choices impact a robots functions in society. In this chapter, we discuss what it means for a robot to be embodied, situated, and to have morphology. Further, we consider relevant HRI research alongside research that underscores the need for roboticists to integrate embodied cognition, situatedness, and morphology in robotic design. For example, research findings demonstrate a materially embodied design that accounts for situatedness as a necessary element for eliciting positive perception of a robot agent. Moreover, we expand on the need for the robotics field to extend its empirical research with varying degrees of implementation that disassociate and control for design factors to distinguish which particular elements provoke positive, neutral, or negative effects in HRI. Without a more robust literature base to discern the most effective forms of robotics within commonplace applications, it will be difficult to know if the applied robotic forms achieve the most compelling HRI.


Embodiment Morphology Human-Robot Interaction Social Robotics 



The authors would like to acknowledge the financial support of this work by Office of Naval Research (ONR) award #N00014-16-1-2312 and the UNR Provost’s Office (New Scholarly Endevour).


  1. 1.
    S.O. Adalgeirsson, C. Breazeal, Mebot: a robotic platform for socially embodied presence, in Proceedings of the 5th ACM/IEEE international conference on Human-robot interaction (IEEE Press, 2010), pp. 15–22Google Scholar
  2. 2.
    C. Bartneck, J. Reichenbach, A. van Breemen, In your face, robot! The influence of a character’s embodiment on how users perceive its emotional expressions, in Proceedings of the Design and Emotion 2004 Conference, Ankara, 2004Google Scholar
  3. 3.
    W. Bechtel, Explanation: mechanism, modularity, and situated cognition, in The Cambridge Handbook of Situated Cognition, ed. By M. Aydede, P. Robbins (Cambridge University Press, Cambridge, 2009), pp. 155–170Google Scholar
  4. 4.
    J. Blascovich, J. Bailenson, Infinite reality: avatars, eternal life, new worlds, and the dawn of the virtual revolution. Presence 20(5), 502–502 (2011) ISSN:1054-7460. Scholar
  5. 5.
    M. Blow, K. Dautenhahn, A. Appleby, C.L. Nehaniv, D.C. Lee, Perception of robot smiles and dimensions for human-robot interaction design, in ROMAN 2006 – The 15th IEEE International Symposium on Robot and Human Interactive Communication, Sept 2006, pp. 469–474.
  6. 6.
    J. Bongard, The utility of evolving simulated robot morphology increases with task complexity for object manipulation. Artif. Life 16(3), 201–223 (2010). Scholar
  7. 7.
    C. Breazeal, A. Brooks, J. Gray, G. Hoffman, C. Kidd, H. Lee, J. Lieberman, A. Lockerd, D. Chilongo, Tutelage and collaboration for humanoid robots. Int. J. Humanoid Rob. 1(02), 315–348 (2004)CrossRefGoogle Scholar
  8. 8.
    R.A. Brooks, Elephants don’t play chess. Robot. Auton. Syst. 6(1–2), 3–15 (1990). ISSN:0921-8890. Scholar
  9. 9.
    A. Butchibabu, C. Sparano-Huiban, L. Sonenberg, J. Shah, Implicit coordination strategies for effective team communication. Hum. Factors J. Hum. Factors Ergon. Soc. 58(4), 595–610 (2016)CrossRefGoogle Scholar
  10. 10.
    A. Cangelosi, T. Ogata, Speech and language in humanoid robots, in Humanoid Robotics: A Reference (Springer, London, 2018)Google Scholar
  11. 11.
    Z. Carlson, L. Lemmon, M. Higgins, D. Frank, D. Feil-Seifer, This robot stinks! differences between perceived mistreatment of robot and computer partners. J. Hum. Robot Interact. (arXiv submission)Google Scholar
  12. 12.
    A. Clark, Being There: Putting Brain, Body, and World Together Again (MIT Press, 1998). ISBN:978-0-262-53156-6Google Scholar
  13. 13.
    A. De Beir, B. Vanderboght, Evolutionary method for robot morphology: case study of social robot probo, in The Eleventh ACM/IEEE International Conference on Human Robot Interaction, HRI’2016, Piscataway (IEEE Press, 2016), pp. 609–610. ISBN:978-1-4673-8370-7.
  14. 14.
    C.F. DiSalvo, F. Gemperle, J. Forlizzi, S. Kiesler, All robots are not created equal: the design and perception of humanoid robot heads, in Proceedings of the 4th Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques, DIS’02, New York (ACM, 2002), pp. 321–326. ISBN:1-58113-515-7.
  15. 15.
    B. Duffy, G. Joue, Intelligent robots: the question of embodiment, in Brain-Machine Workshop, Ankara, 2000Google Scholar
  16. 16.
    B.R. Duffy, Anthropomorphism and the social robot. Robot. Auton. Syst. 42(3–4), 177–190 (2003). ISSN:0921-8890. Socially Interactive RobotsCrossRefGoogle Scholar
  17. 17.
    J. Fasola, M. Mataric, A socially assistive robot exercise coach for the elderly. J. Hum. Robot Interact. 2(2), 3–32 (2013)Google Scholar
  18. 18.
    D. Feil-Seifer, The tail; shouldn’t way the dog: why modeling dog-human interaction is not ideal for socially assistive robotics. Interact. Stud. 15(2), 195–200 (2014)CrossRefGoogle Scholar
  19. 19.
    D. Feil-Seifer, M. Matarić, Defining socially assistive robotics, in International Conference on Rehabilitation Robotics (ICORR), Chicago, June 2005, pp. 465–468.
  20. 20.
    D. Feil-Seifer, M. Matarić, Ethical principles for socially assistive robotics. IEEE Robot. Autom. Mag. 18(1), 24–31 (2011). Scholar
  21. 21.
    D. Feil-Seifer, M. Matarić, Distance-based computational models for facilitating robot interaction with children. J. Hum. Robot Interact. 1(1), 55–77 (2012).
  22. 22.
    J. Fink, Anthropomorphism and human likeness in the design of robots and human-robot interaction, in Proceedings of the 4th International Conference on Social Robotics, ICSR’12, Berlin/Heidelberg (Springer, 2012), pp. 199–208. ISBN:978-3-642-34102-1. Scholar
  23. 23.
    M.E. Foster, M. Giuliani, A. Isard, Task-based evaluation of context-sensitive referring expressions in human – robot dialogue. Lang. Cogn. Neurosci. 29(8), 1018–1034 (2014)CrossRefGoogle Scholar
  24. 24.
    J. Fox, S.J. Ahn, J.H. Janssen, L. Yeykelis, K.Y. Segovia, J.N. Bailenson, Avatars versus agents: a meta-analysis quantifying the effect of agency on social influence. Hum. Comput. Interact. 30(5), 401–432 (2015)CrossRefGoogle Scholar
  25. 25.
    K. Gold, M. Doniec, B. Scassellati, Learning grounded semantics with word trees: prepositions and pronouns, in IEEE 6th International Conference on Development and Learning. ICDL 2007 (IEEE, 2007), pp. 25–30Google Scholar
  26. 26.
    A. Hornung, S. Böttcher, J. Schlagenhauf, C. Dornhege, A. Hertle, M. Bennewitz, Mobile manipulation in cluttered environments with humanoids: integrated perception, task planning, and action execution, in 2014 14th IEEE-RAS International Conference on Humanoid Robots (Humanoids) (IEEE, 2014), pp. 773–778Google Scholar
  27. 27.
    C. Jung, L. Strother, D. Feil-Seifer, J. Hustler, Atypical asymmetry for processing human and robot faces in autism revealed by fNIRS. PLoS One 11(7), 1–13 (2016). Scholar
  28. 28.
    C.D.F.B. Katrin Solveig Lohan, H. Lehmann, H. Kose, Enriching the human robot interaction loop with natural, semantic and symbolic gestures, in Humanoid Robotics: A Reference (Springer, London, 2018)Google Scholar
  29. 29.
    A. Kerepesi, E. Kubinyi, G. Jonsson, M. Magnusson, Á. Miklósi, Behavioural comparison of human-animal (dog) and human-robot (aibo) interactions. Behav. Process. 73(1), 92–99 (2006). ISSN:0376-6357. Scholar
  30. 30.
    S. Kiesler, A. Powers, S. Fussel, C. Torrey, Anthropomorphic interactions with a robot and robot-like agent. Soc. Cogn. 26, 169–181 (2008). ISSN:0278-016X. Scholar
  31. 31.
    H. Kose-Bagci, E. Ferrari, K. Dautenhahn, D.S. Syrdal, C.L. Nehaniv, Effects of embodiment and gestures on social interaction in drumming games with a humanoid robot. Adv. Robot. 23(14), 1951–1996 (2009)CrossRefGoogle Scholar
  32. 32.
    M.V. Liarokapis, P.K. Artemiadis, K.J. Kyriakopoulos, Quantifying anthropomorphism of robot hands, pp. 2041–2046 (2013). ISBN:9781467356411.
  33. 33.
    J. Lindblom, Embodied Social Cognition. Cognitive Systems Monographs (Springer, Cham, 2015). ISBN:9783319203157. Scholar
  34. 34.
    J. Lindblom, T. Ziemke, Social situatedness of natural and artificial intelligence: vygotsky and beyond. Adapt. Behav. 11(2), 79–96 (2003). Scholar
  35. 35.
    H. Lucas, J. Poston, N. Yocum, Z. Carlson, D. Feil-Seifer, Too big to be mistreated? Examining the role of robot size on perceptions of mistreatment, in IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), New York, Aug 2016, pp. 1071–1076. ISBN:978-1-5090-3928-9.
  36. 36.
    H. Maturana, F.J. Varela, Autopoiesis and Cognition – The Realization of the Living, 1980. ISBN:978-90-277-1015-4. Scholar
  37. 37.
    C.I. Mavrogiannis, M.V. Liarokapis, K.J. Kyriakopoulos, Quantifying anthropomorphism of robot arms, in 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sept 2015, pp. 4084–4089.
  38. 38.
    M. Mori, Bukimi no tani (The Uncanny Valley). Energy 7, 33–35 (1970)Google Scholar
  39. 39.
    J. Morkes, H.K. Kernal, C. Nass, Effects of humor in task-oriented human-computer interaction and computer-mediated communication: a direct test of SRCT theory. Hum. Comput. Interact. 14(4), 395–435 (1999). ISSN:0737-0024. Scholar
  40. 40.
    T. Nomura, Empathy as signaling feedback between (humanoid) robots and humans, in Humanoid Robotics: A Reference (Springer, London, 2018)Google Scholar
  41. 41.
    S. Penny, Art and robotics: sixty years of situated machines. AI Soc. 28(2), 147–156 (2013)CrossRefGoogle Scholar
  42. 42.
    R. Perrone, F. Nessi, E. De Momi, F. Boriero, M. Capiluppi, P. Fiorini, G. Ferrigno, Ontology-based modular architecture for surgical autonomous robots, in The Hamlyn Symposium on Medical Robotics, 2014, p. 85Google Scholar
  43. 43.
    R. Pfeifer, C. Scheier, Understanding Intelligence (MIT Press, Cambridge, 1999)Google Scholar
  44. 44.
    K. Pitsch, Limits and opportunities for mathematizing communicational conduct for social robotics in the real world? Toward enabling a robot to make use of the human’s competences. AI Soc. 31(4), 587–593 (2016). ISSN:1435-5655. Scholar
  45. 45.
    A. Prakash, W.A. Rogers, Why some humanoid faces are perceived more positively than others: effects of human-likeness and task. Int. J. Soc. Robot. 7(2), 309–331 (2015). ISSN:1875-4805. Scholar
  46. 46.
    I. Rae, L. Takayama, B. Mutlu, In-body experiences: embodiment, control, and trust in robot-mediated communication, in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (ACM, 2013), pp. 1921–1930Google Scholar
  47. 47.
    G. Rickheit, I. Wachsmuth, Collaborative Research Centre “Situated Artificial Communicators” at the University of Bielefeld (Springer Netherlands, Dordrecht, 1996), pp. 165–170. ISBN 978-94-009-1716-3. Scholar
  48. 48.
    A. Riegler, When is a cognitive system embodied? Cogn. Syst. Res. special issue on “Situ- ated and Embodied Cognition” 3, 339–348 (2002). Scholar
  49. 49.
    A.M. Rosenthal-von der Pütten, N.C. Krämer, How design characteristics of robots determine evaluation and uncanny valley related responses. Comput. Hum. Behav. 36, 422–439 (2014)Google Scholar
  50. 50.
    A.D. Santis, B. Siciliano, A.D. Luca, A. Bicchi, An atlas of physical human-robot interaction. Mech. Mach. Theory 43(3), 253–270 (2008). ISSN:0094-114X.; Scholar
  51. 51.
    A.P. Saygin, T. Chaminade, H. Ishiguro, J. Driver, C. Frith, The thing that should not be: predictive coding and the uncanny valley in perceiving human and humanoid robot actions. Soc. Cogn. Affect. Neurosci. 7(4), 413 (2012). Scholar
  52. 52.
    D.P.A.C. Schultz, W. Adams, E. Marsh, M. Bugajska, Building a multimodal human-robot interface. IEEE Intell. Syst. 16(1), 16–21 (2001)CrossRefGoogle Scholar
  53. 53.
    J. Seyama, R.S. Nagayama, The uncanny valley: effect of realism on the impression of artificial human faces. Presence 16(4), 337–351 (2007). ISSN:1054-7460. Scholar
  54. 54.
    N. Sharkey, T. Ziemke, Life, Mind, and Robots (Springer, Berlin/Heidelberg, 2000). ISBN: 978-3-540-67305-7. Scholar
  55. 55.
    M.J. Spivey, K. McRae, M.H. Fischer, A. Cangelosi, L.W. Barsalou, G. Pezzulo, The mechanics of embodiment: a dialog on embodiment and computational modeling. Front. Psychol. 2, 5 (2011).
  56. 56.
    M. Stapleton, Steps to a “properly embodied” cognitive science. Cogn. Syst. Res. 22–23, 1–11 (2013). ISSN: 1389-0417. Scholar
  57. 57.
    L.A. Suchman, Plans and Situated Actions: The Problem of Human-machine Communication (Cambridge University Press, New York, 1987). ISBN:0-521-33137-4Google Scholar
  58. 58.
    J. von Uexküll, The Theory of Meaning, 2009, pp. 25–79. ISBN:0037-1998.
  59. 59.
    J. Wainer, D. Feil-Seifer, D.A. Shell, M. Matarić, The role of physical embodiment in human-robot interaction, in IEEE Proceedings of the International Workshop on Robot and Human Interactive Communication (RO-MAN), Hatfield, Sept 2006, pp. 117–122.
  60. 60.
    J. Wainer, D. Feil-Seifer, D.A. Shell, M. Matarić, Embodiment and human-robot interaction: a task-based perspective, in IEEE Proceedings of the International Workshop on Robot and Human Interactive Communication (RO-MAN), Jeju Island, Aug 2007, pp. 872–877.
  61. 61.
    M. Wilson, Six views of embodied cognition. Psychon. Bull. Rev. 9(4), 625–636 (2002). ISSN:1531-5320. Scholar
  62. 62.
    K. Zivin, A. Sen, M.A. Plegue, M.L. Maciejewski, M.L. Segar, M. AuYoung, E.M. Miller, C.A. Janney, D.M. Zulman, C.R. Richardson, Comparative effectiveness of wellness programs: impact of incentives on healthcare costs for obese enrollees. Am. J. Prev. Med. 52(3), 347–352 (2016)CrossRefGoogle Scholar
  63. 63.
    J. Złotowski, E. Strasser, C. Bartneck, Dimensions of anthropomorphism: from humanness to humanlikeness, in Proceedings of the 2014 ACM/IEEE International Conference on Human-robot Interaction, HRI’14, New York (ACM, 2014), pp. 66–73. ISBN:978-1-4503-2658-2.

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© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Computer Science & EngineeringUniversity of Nevada, RenoRenoUSA

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