Skip to main content
SpringerLink
Log in

Benchmarking in Developmental Robotics

  • Chapter
  • First Online:
Metrics of Sensory Motor Coordination and Integration in Robots and Animals

Part of the book series: Cognitive Systems Monographs ((COSMOS,volume 36))

  • 419 Accesses

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://www.robocupatwork.org/.

  2. 2.

    http://www.robocup.org/.

  3. 3.

    By simple transfer we mean the way that the infant can still be successful if lighting conditions are altered, or the toy to be retrieved is changed slightly, or the table surface texture is changed, etc.

  4. 4.

    There are not many examples of works in developmental robotics which compare with infant scales of development, although Kido et al. [18] do compare with the Kyoto Scale of Psychological Development. This scale however appears to be only available in Japanese.

  5. 5.

    http://www.robocupathome.org/rules.

  6. 6.

    See for example the EU FP7 Xperience project [1]: http://www.xperience.org/.

  7. 7.

    The Cognitive and Developmental Systems Technical Committee (CDSTC) of the Computational Intelligence Society (CIS) of the IEEE would be an obvious parent organisation.

References

  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. 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)

    Article  Google Scholar 

  3. Bower, T.G.R.: Development in Infancy. W.H. Freeman, San Francisco (1982)

    Google Scholar 

  4. Brown, A.L.: Domain-specific principles affect learning and transfer in children. Cogn. Sci. 14(1), 107–133 (1990)

    Google Scholar 

  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)

    Article  Google Scholar 

  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)

    Article  Google Scholar 

  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. Claxton, L., Keen, R., McCarty, M.: Evidence of motor planning in infant reaching behavior. Psychol. Sci. 14(4), 354–356 (2003)

    Article  Google Scholar 

  9. Cohen, P.: If not Turings test, then what? AI Magazine 26(4), (2006)

    Google Scholar 

  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)

    Article  Google Scholar 

  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. 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. Funk, M.S.: Problem solving skills in young yellow-crowned parakeets (cyanoramphus auriceps). Anim. Cogn. 5, 167–176 (2002)

    Article  Google Scholar 

  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. 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)

    Article  Google Scholar 

  16. Hart, S., Grupen, R.: Learning generalizable control programs. IEEE Trans. Auton. Ment. Dev. 3(3), 216–231 (2011)

    Article  Google Scholar 

  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. 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. 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. Lungarella, M., Metta, G., Pfeifer, R., Sandini, G.: Developmental robotics: a survey. Connection Sci. 15(4D), 151–190 (2003)

    Article  Google Scholar 

  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)

    Article  Google Scholar 

  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)

    Article  Google Scholar 

  23. Oudeyer, P.-Y., Kaplan, F., Hafner, V.: Intrinsic motivation systems for autonomous mental development. IEEE Trans. Evol. Comput. 11(6), 265–286 (2007)

    Article  Google Scholar 

  24. Piaget, J.: The Origins of Intelligence in Children. Routledge & Kegan Paul, London (1936). French version 1936, translation 1952

    Google Scholar 

  25. Piaget, J.: The Construction of Reality in the Child. Routledge & Kegan Paul, London (1937). French version 1937, translation 1955

    Google Scholar 

  26. Piaget, J.: Play, Dreams and Imitation in Childhood. Heinemann, London (1945)

    Google Scholar 

  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. 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)

    Article  Google Scholar 

  29. Rosman, B., Ramamoorthy, S.: Learning spatial relationships between objects. Int. J. Robot. Res. 30(11), 1328–1342 (2011)

    Article  Google Scholar 

  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. 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)

    Article  Google Scholar 

  32. Turing, A.M.: Computing machinery and intelligence. Mind 59, 433–460 (1950)

    Article  MathSciNet  Google Scholar 

  33. Ugur, E., Oztop, E., Sahin, E.: Goal emulation and planning in perceptual space using learned affordances (2011)

    Google Scholar 

  34. Uzgiris, I.C., Hunt, J.M.: Assessment in Infancy: Ordinal Scales of Psychological Development. University of Illinois Press, Urbana (1975)

    Google Scholar 

Download references

Acknowledgements

Thanks to Norbert Krüger for comments on a draft.

Author information

Authors and Affiliations

  1. University of Aberdeen, King’s College, Aberdeen, AB24 3UE, Scotland

    Frank Guerin

  2. Laboratoire Ethologie Cognition Développement, Université Paris Nanterre, 200 avenue de la République, 92001, Nanterre Cedex, France

    Lauriane Rat-Fischer

Authors
  1. Frank Guerin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lauriane Rat-Fischer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Frank Guerin .

Editor information

Editors and Affiliations

  1. Institute of Biorobotics, Scuola Superiore Sant’Anna, Pisa, Italy

    Fabio Bonsignorio

  2. Intelligent Systems Division, Manipulation and Mobility Systems Group, National Institute of Standards and Technology, Gaithersburg, MD, USA

    Elena Messina

  3. Robotic Intelligence Laboratory, Department of Computer Science and Engineering, Universidad Jaume I, Castellón de la Plana, Spain

    Angel P. del Pobil

  4. Mærsk Mc-Kinney Møller Institute, University of Southern Denmark, Odense, Denmark

    John Hallam

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Guerin, F., Rat-Fischer, L. (2020). Benchmarking in Developmental Robotics. In: Bonsignorio, F., Messina, E., del Pobil, A., Hallam, J. (eds) Metrics of Sensory Motor Coordination and Integration in Robots and Animals. Cognitive Systems Monographs, vol 36. Springer, Cham. https://doi.org/10.1007/978-3-030-14126-4_4

Download citation

Publish with us

Policies and ethics

Search

Navigation