Abstract
A computational theory model is constructed to generate a body map and a body schema. It is assumed that the fetus has a body map and a body schema to control and understand its body and generates them based on tactile information obtained by random motion in the womb called general movement. As a first step, in this research, a computational theory model is proposed to generate the body Map based on tactile information and to estimate nodes of the body schema by machine learning methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kuniyoshi, Y., Suzuki, S.: Dynamic emergence and adaptation of behavior through embodiment as coupled chaotic field. In: 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004 (IROS 2004). Proceedings, vol. 2, pp. 2042–2049. IEEE (2004)
Blakeslee, S., Blakeslee, M.: The Body Has a Mind of Its Own: How Body Maps in Your Brain Help You Do (Almost) Everything Better. Random House (2008)
Yamada, Y., Fujii, K., Kuniyoshi, Y.: Impacts of environment, nervous system and movements of preterms on body map development: fetus simulation with spiking neural network. In: IEEE ICDL-EPIROB2013 (2013)
Prechtl, H.F.: State of the art of a new functional assessment of the young nervous system. An early predictor of cerebral palsy. Early Human Dev. 50(1), 1–11 (1997)
Kruskal, J.B.: Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika 29(1), 1–27 (1964)
Gelman, A., Carlin, J.B., Stern, H.S., Rubin, D.B.: Bayesian Data Analysis, vol. 2. Taylor & Francis (2014)
Olsson, L.A., Nehaniv, C.L., Polani, D.: From unknown sensors and actuators to actions grounded in sensorimotor perceptions. Connect. Sci. 18(2), 121–144 (2006)
Mori, H., Kuniyoshi, Y.: A human fetus development simulation: self-organization of behaviours through tactile sensation. In: IEEE 9th International Conference on Development and Learning (ICDL), pp. 82–87 (2010)
Sugiura, K., Matsubara, D., Katai, O.: Construction of robotic body schema by extracting temporal information from sensory inputs. In: SICE-ICASE International Joint Conference, pp. 302–307 (2006)
Kuniyoshi, Y., Yorozu, Y., Ohmura, Y., Terada, K., Otani, T., Nagakubo, A., Yamamoto, T.: From humanoid embodiment to theory of mind. In: Embodied Artificial Intelligence, pp. 202–218. Springer (2004)
Gallagher, S.: Body image and body schema: a conceptual clarification. J. Mind Behav. 7(4), 5417554 (1986)
Martinez-Cantin, R., Lopes, M., Montesano, L.: Body schema acquisition through active learning. In: 2010 IEEE International Conference on Robotics and Automation (ICRA), pp. 1860–1866. IEEE (2010)
Olsson, L., Nehaniv, C.L., Polani, D.: Measuring informational distances between sensors and sensor integration. In: Artificial Life X. MIT Press (2006)
Bishop, C.M.: Pattern Recognition and Machine Learning. Springer (2006)
Sethuraman, J.: A constructive definition of dirichlet priors. Technical Report, DTIC Document (1991)
Smith, R.: Open dynamics engine. http://www.ode.org/
Hubert, L., Arabie, P.: Comparing partitions. J. Classif. 2(1), 193–218 (1985)
Ward Jr., J.H.: Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc. 58(301), 236–244 (1963)
Yeung, K.Y., Ruzzo, W.L.: Details of the adjusted rand index and clustering algorithms, supplement to the paper an empirical study on principal component analysis for clustering gene expression data. Bioinformatics 17(9), 763–774 (2001)
Acknowledgements
This research was partially supported by a Grant-in-Aid for Scientific Research on Innovative Areas 2015–2017 (15H01670) funded by the Ministry of Education, Culture, Sports, Science, and Technology, Japan.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Mimura, T., Hagiwara, Y., Taniguchi, T., Inamura, T. (2017). Clustering Latent Sensor Distribution on Body Map for Generating Body Schema. In: Chen, W., Hosoda, K., Menegatti, E., Shimizu, M., Wang, H. (eds) Intelligent Autonomous Systems 14. IAS 2016. Advances in Intelligent Systems and Computing, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-319-48036-7_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-48036-7_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-48035-0
Online ISBN: 978-3-319-48036-7
eBook Packages: EngineeringEngineering (R0)