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Robot Programming Through Whole-Body Interaction

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Book cover Progress in Artificial Intelligence (EPIA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10423))

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Abstract

Programmable and non-programmable educational robots are, in most cases, associated with sedentary behavior in children. Children interact with educational robots mostly in indoor environments. Whole-body interaction and natural environments seem to potentiate children’s physical and mental health. In order to potentiate children’s physical and mental health we have developed a new set of robotic devices - Biosymtic Robotic devices. We describe the main computational models of Biosymtic Robotic devices: a computational model demonstrating how to increase children’s physical activity levels and contact with natural environments through automatic feedback control mechanisms; a theoretical cognitive model on how to program robotic devices through whole-body interaction in natural environments.

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References

  1. American Heart Association 2015. Target Heart Rates. http://www.heart.org/HEARTORG/GettingHealthy/PhysicalActivity/FitnessBasics/Target-Heart-Rates_UCM_434341_Article.jsp

  2. Bar-Cohen, Y., Breazeal, C.: Biologically inspired intelligent robotics. In: Proceedings of the SPIE Smart Structures Conference, San Diego, CA, pp. 1–7 (2003)

    Google Scholar 

  3. Barsalou, L.W.: Perceptual symbol systems. Behav. Brain Sci. 22(4), 577–660 (1999)

    Article  Google Scholar 

  4. Boreham, C., Riddoch, C.: The physical activity, fitness and health of children. J. Sports Sci. 19(12), 915–929 (2001)

    Article  Google Scholar 

  5. Calinon, S., Billard, A.: What is the teacher’s role in robot programming by demonstration? Toward benchmarks for improved learning. Interact. Stud. 8(3), 441–464 (2007). Special Issue on Psychological Benchmarks in Human-Robot Interaction

    Article  Google Scholar 

  6. Chaddock, L., Erickson, K.I., Prakash, R.S., Kim, J.S., Voss, M.W., Vanpatter, M., Kramer, A.F.: A neuroimaging investigation of the association between aerobic fitness, hippocampal volume and memory performance in preadolescent children. Brain Res. 1358, 172–183 (2010)

    Article  Google Scholar 

  7. Espinoza, R.R., Nalin, M., Wood, R., Baxter, P., Looije, R., Demiris, Y.: Child-robot interaction in the wild: advice to the aspiring experimenter. In: Proceedings of the 13th International Conference on Multimodal Interfaces, ICMI 2011, pp. 335–342. ACM (2011)

    Google Scholar 

  8. Removed for blind review 2016

    Google Scholar 

  9. Removed for blind review 2017

    Google Scholar 

  10. Grigore, E.C., Scassellati, B.: Maintaining engagement in shared goals with a personal robot companion through motivational state modeling. In: 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Portland, OR (2015)

    Google Scholar 

  11. Jensen, E.: Learning with the Body in the Mind: The Scientific Basis for Energizers, Movement, Play, Games, and Physical Education. The Brain Store, Inc., Chicago (2000)

    Google Scholar 

  12. Kirstein, F., Risager, R.V.: Social robots in educational institutions. They came to stay: introducing, evaluating, and securing social robots in daily education. In: The Eleventh ACM/IEEE International Conference on Human-Robot Interaction, HRI 2016, pp. 453–454. IEEE Press, Piscataway (2016)

    Google Scholar 

  13. Meyer, J.-A., Guillot, A.: Biologically inspired robots. In: Siciliano, B., Khatib, O. (eds.) Springer Handbook of Robotics, pp. 1395–1422. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  14. Minsky, M.L.: Robotics. Omni Press Book, New York (1985)

    Google Scholar 

  15. von Neumann, J.: Theory of Self-Reproducing Automata. Burks, A.W. (ed.) University of Illinois Press, Urbana and London (1966)

    Google Scholar 

  16. Papert, S.: Mindstorms, Children, Computers and Powerful Ideas, 2nd edn. Basic Books, New York (1980)

    Google Scholar 

  17. Piek, J.P., Dawson, L., Smith, L.M., Gasson, N.: The role of early fine and gross motor development on later motor and cognitive ability. Hum. Mov. Sci. 27(5), 668–681 (2008)

    Article  Google Scholar 

  18. World Health Organization 2013. Physical Activity and Young People. http://www.who.int/dietphysicalactivity/factsheet_young_people/en/

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Correspondence to Marta Ferraz .

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Ferraz, M. (2017). Robot Programming Through Whole-Body Interaction. In: Oliveira, E., Gama, J., Vale, Z., Lopes Cardoso, H. (eds) Progress in Artificial Intelligence. EPIA 2017. Lecture Notes in Computer Science(), vol 10423. Springer, Cham. https://doi.org/10.1007/978-3-319-65340-2_13

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  • DOI: https://doi.org/10.1007/978-3-319-65340-2_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-65339-6

  • Online ISBN: 978-3-319-65340-2

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