Benchmarking in Developmental Robotics

  • Frank GuerinEmail author
  • Lauriane Rat-Fischer
Part of the Cognitive Systems Monographs book series (COSMOS, volume 36)


There is at present no standard benchmarking for assessing and comparing the various existing works in developmental robotics. Developmental robotics is more of a “basic science” research endeavour than mainstream robotics, which is more application focussed. For this reason benchmarking for developmental robotics will need a more scientific basis, rather than a specific application focus. The solution we propose is to benchmark developmental robotics efforts against human infant capabilities at various ages. The proposal here may allow the community to showcase their efforts by demonstration on common tasks, and so to enable the comparison of approaches. It may also provide an agenda of incremental targets for research in the field.



Thanks to Norbert Krüger for comments on a draft.


  1. 1.
    Aksoy, E.E., Tamosiunaite, M., Vuga, R., Ude, A., Geib, C., Steedman, M., Wörgötter, F.: Structural bootstrapping at the sensorimotor level for the fast acquisition of action knowledge for cognitive robots. In: IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL) (2013)Google Scholar
  2. 2.
    Asada, M., Hosoda, K., Kuniyoshi, Y., Ishiguro, H., Inui, T., Yoshikawa, Y., Ogino, M., Yoshida, C.: Cognitive developmental robotics: a survey. IEEE Trans. Auton. Ment. Dev. 1(1), 12–34 (2009)CrossRefGoogle Scholar
  3. 3.
    Bower, T.G.R.: Development in Infancy. W.H. Freeman, San Francisco (1982)Google Scholar
  4. 4.
    Brown, A.L.: Domain-specific principles affect learning and transfer in children. Cogn. Sci. 14(1), 107–133 (1990)Google Scholar
  5. 5.
    Bushnell, E.W., Boudreau, J.P.: Motor development and the mind: the potential role of motor abilities as a determinant of aspects of perceptual development. Child Dev. 64(4), 1005–1021 (1993)CrossRefGoogle Scholar
  6. 6.
    Cangelosi, A., Metta, G., Sagerer, G., Nolfi, S., Nehaniv, C., Fischer, K., Tani, J., Belpaeme, T., Sandini, G., Nori, F., Fadiga, L., Wrede, B., Rohlfing, K., Tuci, E., Dautenhahn, K., Saunders, J., Zeschel, A.: Integration of action and language knowledge: a roadmap for developmental robotics. IEEE Trans. Auton. Ment. Dev. 2(3), 167–195 (2010)CrossRefGoogle Scholar
  7. 7.
    Chen, Z., Siegler, R.S., Daehler, M.W.: Across the great divide: Bridging the gap between understanding of toddlers’ and older children’s thinking. Monogr. Soc. Res. Child Dev. 65(2), i–105 (2000)Google Scholar
  8. 8.
    Claxton, L., Keen, R., McCarty, M.: Evidence of motor planning in infant reaching behavior. Psychol. Sci. 14(4), 354–356 (2003)CrossRefGoogle Scholar
  9. 9.
    Cohen, P.: If not Turings test, then what? AI Magazine 26(4), (2006)Google Scholar
  10. 10.
    Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: The PASCAL visual object classes (VOC) challenge. Int. J. Comput. Vis. 88(2), 303–338 (2010)CrossRefGoogle Scholar
  11. 11.
    Fagard, J., Rat-Fischer, L., O’Regan, J.K.: The emergence of use of a rake-like tool: a longitudinal study in human infants. Front. Psychol. 5(491), (2014)Google Scholar
  12. 12.
    Fichtl, S., Alexander, J., Kraft, D., Jorgensen, J., Krüger, N., Guerin, F.: Learning object relationships which determine the outcome of actions. Paladyn 3(4), 188–199 (2012)Google Scholar
  13. 13.
    Funk, M.S.: Problem solving skills in young yellow-crowned parakeets (cyanoramphus auriceps). Anim. Cogn. 5, 167–176 (2002)CrossRefGoogle Scholar
  14. 14.
    Guadarrama, S., Riano, L., Golland, D., Göhring, D., Jia, Y., Klein, D., Abbeel, P., Darrell, T.: Grounding spatial relations for human-robot interaction. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (2013)Google Scholar
  15. 15.
    Guerin, F., Kruger, N., Kraft, D.: A survey of the ontogeny of tool use: from sensorimotor experience to planning. IEEE Trans. Auton. Ment. Dev. 5(1), 18–45 (2013)CrossRefGoogle Scholar
  16. 16.
    Hart, S., Grupen, R.: Learning generalizable control programs. IEEE Trans. Auton. Ment. Dev. 3(3), 216–231 (2011)CrossRefGoogle Scholar
  17. 17.
    Itauma, I., Kivrak, H., Kose, H.: Gesture imitation using machine learning techniques. In: 2012 20th Signal Processing and Communications Applications Conference (SIU), pp. 1–4 (2012)Google Scholar
  18. 18.
    Kido, M., Itoh, H., Fukumoto, H., Wakuya, H., Furukawa, T.: Developing a robot that performs tasks of developmental scales: on gaze control by eye-head coordination. In: 2011 Proceedings of SICE Annual Conference (SICE), pp. 2488–2491 (2011)Google Scholar
  19. 19.
    Law, J., Shaw, P., Earland, K., Sheldon, M., Lee, M.H.: A psychology based approach for longitudinal development in cognitive robotics. Front. Neurorobotics 8(1) (2014)Google Scholar
  20. 20.
    Lungarella, M., Metta, G., Pfeifer, R., Sandini, G.: Developmental robotics: a survey. Connection Sci. 15(4D), 151–190 (2003)CrossRefGoogle Scholar
  21. 21.
    McCarty, M.E., Clifton, R.K., Ashmead, D.H., Lee, P., Goubet, N.: How infants use vision for grasping objects. Child Dev. 72(4), 973–987 (2001)CrossRefGoogle Scholar
  22. 22.
    McCarty, M.E., Clifton, R.K., Collard, R.R.: Problem solving in infancy: the emergence of an action plan. Dev. Psychol. 35(4), 1091–1101 (1999)CrossRefGoogle Scholar
  23. 23.
    Oudeyer, P.-Y., Kaplan, F., Hafner, V.: Intrinsic motivation systems for autonomous mental development. IEEE Trans. Evol. Comput. 11(6), 265–286 (2007)CrossRefGoogle Scholar
  24. 24.
    Piaget, J.: The Origins of Intelligence in Children. Routledge & Kegan Paul, London (1936). French version 1936, translation 1952Google Scholar
  25. 25.
    Piaget, J.: The Construction of Reality in the Child. Routledge & Kegan Paul, London (1937). French version 1937, translation 1955Google Scholar
  26. 26.
    Piaget, J.: Play, Dreams and Imitation in Childhood. Heinemann, London (1945)Google Scholar
  27. 27.
    Prince, C., Helder, N., Hollich, G.: Ongoing emergence: a core concept in epigenetic robotics. In: Berthouze, L., Kaplan, F., Kozima, H., Yano, H., Konczak, J., Metta, G., Nadel, J., Sandini, G., Stojanov, G., Balkenius, C. (eds) Proceedings of EpiRob’05 - International Conference on Epigenetic Robotics, pp. 63–70. Lund University Cognitive Studies (2005)Google Scholar
  28. 28.
    Rat-Fischer, L., O’Regan, J., Fagard, J.: The emergence of tool use during the second year of life. Exp Child Psychol. 113(3), 440–446 (2012)CrossRefGoogle Scholar
  29. 29.
    Rosman, B., Ramamoorthy, S.: Learning spatial relationships between objects. Int. J. Robot. Res. 30(11), 1328–1342 (2011)CrossRefGoogle Scholar
  30. 30.
    Schmidhuber, J.: A possibility for implementing curiosity and boredom in model-building neural controllers. In: The International Conference on Simulation of Adaptive Behavior: From Animals to Animats, pp. 222–227 (1991)Google Scholar
  31. 31.
    Streri, A., Féron, J.: The development of haptic abilities in very young infants: from perception to cognition. Infant Behav. Dev. 28(3), 290–304 (2005)CrossRefGoogle Scholar
  32. 32.
    Turing, A.M.: Computing machinery and intelligence. Mind 59, 433–460 (1950)MathSciNetCrossRefGoogle Scholar
  33. 33.
    Ugur, E., Oztop, E., Sahin, E.: Goal emulation and planning in perceptual space using learned affordances (2011)Google Scholar
  34. 34.
    Uzgiris, I.C., Hunt, J.M.: Assessment in Infancy: Ordinal Scales of Psychological Development. University of Illinois Press, Urbana (1975)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University of Aberdeen, King’s CollegeAberdeenScotland
  2. 2.Laboratoire Ethologie Cognition DéveloppementUniversité Paris NanterreNanterre CedexFrance

Personalised recommendations