This chapter discusses android science as an interdisciplinary framework bridging robotics and cognitive science. Android science is expected to be a fundamental research area in which the principles of human-human communications and human-robot communications are studied. In the framework of android science, androids enable us to directly exchange bodies of knowledge gained by the development of androids in engineering and the understanding of humans in cognitive science. As an example of practice in android science, this chapter introduces geminoids, very humanlike robots modeled on real persons, and explains how body ownership transfer occurs for the operator of a geminoid. The phenomenon of body ownership transfer is studied with a geminoid and a brain-machine interface system.


Human-robot interaction The behavior-based system Distributed cognition Constructive approach Android science Total Turing test Total intelligence Android Uncanny valley Geminoid Body ownership transfer Rubber hand illusion Brain-machine interface Brain-machine interface (BMI) system 


  1. Alimardani, M., Nishio, S., Ishiguro, H.: Humanlike robot hands controlled by brain activity arouse illusion of ownership in operators. Sci. Rep. 3, 2396 (2013)CrossRefGoogle Scholar
  2. Armel, K., Ramachandran, V.: Projecting sensations to external objects: evidence from skin conductance response. Proc. Biol. Sci. 270(1523), 1499–1506 (2003)CrossRefGoogle Scholar
  3. Botvinick, M.: Rubber hands ‘feel’ touch that eyes see. Nature 391(6669), 756 (1998)CrossRefGoogle Scholar
  4. Brooks, R.: Intelligence without representation. Artif. Intell. 47, 139–159 (1991)CrossRefGoogle Scholar
  5. Chapman, C., Jiang, W., Lamarre, Y.: Modulation of lemniscal input during conditioned arm movements in the monkey. Exp. Brain Res. 72, 316–334 (1988)CrossRefGoogle Scholar
  6. Ehrsson, H.: The experimental induction of out-of-body experiences. Science 317, 1048 (2007)CrossRefGoogle Scholar
  7. Ehrsson, H., Holmes, N., Passingham, R.: Touching a rubber hand: feeling of body ownership is associated with activity in multisensory brain areas. J. Neurosci. 25, 10564–10573 (2005)CrossRefGoogle Scholar
  8. Harnad, S.: The symbol grounding problem. Phys. D 42, 335–346 (1990)CrossRefGoogle Scholar
  9. Hashimoto, T., Hiramatsu, S., Kobayashi, H.: Development of face robot for emotional communication between human and robot. In: Proceedings of the IEEE International Conference on Mechatronics and Automation, (2006)Google Scholar
  10. Hollan, J., Hutchins, E., Kirsh, D.: Distributed cognition: toward a new foundation for human-computer interaction research. ACM Trans. Comput. Hum. Interact. 7(2), 174–196 (2000)CrossRefGoogle Scholar
  11. Home page of the Loebner Prize in artificial intelligence, “The first Turing Test,”
  12. Ikeda, T., Ishida, T., Ishiguro, H.: Framework of distributed audition. In: Proceedings of the 13th IEEE International Workshop of Robot and Human Interactive Communication (ROMAN), pp. 77–82, (2004)Google Scholar
  13. Ishiguro, H.: Scientific issues concerning androids. Int. J. Robot. Res. 26(1), 105–117 (2007)CrossRefGoogle Scholar
  14. Ishiguro, H., Nishio, S.: Building artificial humans to understand humans. J. Artif. Organs 10(3), 133–142 (2007)CrossRefGoogle Scholar
  15. Ishiguro, H., Nishimura, T.: VAMBAM: view and motion based aspect models for distributed omnidirectional vision systems. In: Proceedings of the International of the Joint Conference on Artificial Intelligence (IJCAI), pp. 1375–1380, (2001)Google Scholar
  16. Ishiguro, H.: Distributed vision system: a perceptual information infrastructure for robot navigation. In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), pp. 36–41, (1997)Google Scholar
  17. Ishiguro, H., Ono, T., Imai, M., Maeda, T., Kanda, T., Nakatsu, R.: Robovie: an interactive humanoid robot. Int. J. Ind. Robot. 28(6), 498–503 (2001)CrossRefGoogle Scholar
  18. Ishiguro, H.: Toward interactive humanoid robots: a constructive approach to developing intelligent robot. In: Proceedings of the 1st International Joint Conference on the Autonomous Agents and Multiagent Systems, Invited talk, Part 2, pp. 621–622, (2002)Google Scholar
  19. Itakura, S.: Gaze following and joint visual attention in nonhuman animals. Jpn. Psychol. Res. 46, 216–226 (2004)CrossRefGoogle Scholar
  20. Kanda, T., Ishiguro, H., Ishida, T.: Psychological analysis on human-robot interaction. In: Proceedings of IEEE International Conference on Robotics and Automation (ICRA), pp. 4166–4171, (2001)Google Scholar
  21. Kanda, T., Ishiguro, H., Imai, M., Ono, T.: Development and evaluation of interactive humanoid robots. Proc. IEEE 92(11), 1839–1850 (2004)CrossRefGoogle Scholar
  22. Kilner, J., Paulignan, Y., Blakemore, S.: An interference effect of observed biological movement on action. Curr. Biol. 13, 522–525 (2003)CrossRefGoogle Scholar
  23. Lang, P.J., Greenwald, M.K., Bradley, M.M., Hamm, A.O.: Looking at pictures: affective, facial, visceral, and behavioral reactions. Psychophysiology 30, 261–273 (1993)Google Scholar
  24. Lebedev, M., Nicolelis, M.: Brain-machine interfaces: past, present and future. Trends Neurosci. 29, 536–546 (2006)CrossRefGoogle Scholar
  25. Lebedev, M., Denton, J., Nelson, R.: Vibration-entrained and premovement activity in monkey primary somatosensory cortex. J. Neurophysiol. 72, 1654–1673 (1994)Google Scholar
  26. MacDorman, K., Minato, T., Shimada, M., Itakura, S., Cowley, S.J., Ishiguro, H.: Assessing human likeness by eye contact in an android testbed. In: Proceedings of Annual Meeting of the Cognitive Science Society, (2005)Google Scholar
  27. McCarthy, A., Lee, K., Muir, D.: Eye gaze displays that index knowing, thinking and guessing. In: Proceedings of the Annual Conference on American Psychological Society, (2001)Google Scholar
  28. Minato, T., Shimada, M., Itakura, S., Lee, K., Ishiguro, H.: Evaluating the human likeness of an android by comparing gaze behaviors elicited by the android and a person. Adv. Robot. 20, 1147–1163 (2006)CrossRefGoogle Scholar
  29. Mori, M.: Bukimi no tani (the uncanny valley). Energy 7, 33–35 (1970)Google Scholar
  30. Neuper, C., Muller-Putz, G., Scherer, R., Pfurtscheller, G.: Motor imagery and EEG-based control of spelling devices and neuroprostheses. Prog. Brain Res. 159, 393–409 (2006)CrossRefGoogle Scholar
  31. Nishio, S., Ishiguro, H., Hagita, N.: Geminoid: teleoperated android of an existing person. In: de Pina Filho, A. (ed.) Humanoid Robots: New Developments. I-Tech Education and Publishing, Vienna (2007)Google Scholar
  32. Nishio, S., Watanabe, T., Ogawa, K., Ishiguro, H.: Body ownership transfer to teleoperated android robot. In: Paper presented at the International Conference on Social Robotics, pp. 398–407, (2012)Google Scholar
  33. O’Doherty, J., et al.: Active tactile exploration using a brain-machine-brain interface. Nature 479, 228–231 (2011)CrossRefGoogle Scholar
  34. Pavani, F.: Visual capture of touch: out-of-the-body experiences with rubber gloves. Psychol. Sci. 11(5), 353–359 (2000)CrossRefGoogle Scholar
  35. Perani, D., Fazio, F., Borghese, N., Tettamanti, M., Ferrari, S., Decety, J., Gilardi, M.: Different brain correlates for watching real and virtual hand actions. NeuroImage 14, 749–758 (2001)CrossRefGoogle Scholar
  36. Perlin, K.: Real time responsive animation with personality. IEEE Trans. Vis. Comput. Graph. 1(1), 5–15 (1995)CrossRefGoogle Scholar
  37. Personal robot PaPeRo, NEC Co. (Online). Available
  38. Petkova, V., Ehrsson, H.: If I were you: perceptual illusion of body swapping. PLoS One 3, e3832 (2008)CrossRefGoogle Scholar
  39. Prut, Y., Fetz, E.: Primate spinal interneurons show pre-movement instructed delay activity. Nature 401, 590–594 (1999)CrossRefGoogle Scholar
  40. Shimada, S., Fukuda, K., Hiraki, K.: Rubber hand illusion under delayed visual feedback. PLoS One 4(7), e6185 (2009)CrossRefGoogle Scholar
  41. Tsakiris, M.: My body in the brain: a neurocognitive model of body-ownership. Neuropsychologia 48(3), 703–712 (2010)CrossRefGoogle Scholar
  42. Tsakiris, M., Haggard, P., Frank, N., Mainy, N., Sirigu, A.: A specific role for efferent information in self-recognition. Cognition 96, 215–231 (2007)CrossRefGoogle Scholar
  43. Turing, A.: Computing machinery and intelligence. Mind 59, 433–460 (1950)MathSciNetCrossRefGoogle Scholar
  44. Voss, M., Ingram, J., Wolpert, D., Haggard, P.: Mere expectation to move causes attenuation of sensory signals. PLoS One 3, e2866 (2008)CrossRefGoogle Scholar
  45. Walsh, L., Moseley, G., Taylor, J., Gandevia, S.: Proprioceptive signals contribute to the sense of body ownership. J. Physiol. 589, 3009–3021 (2011)CrossRefGoogle Scholar

Copyright information

© Springer Japan 2016

Authors and Affiliations

  1. 1.Graduate School of Engineering ScienceOsaka UniversityToyonakaJapan

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