Abstract
In the field of developmental robotics, a lot of attention has been devoted to algorithms that allow agents to build up skills through sensorimotor interaction. Such interaction is largely affected by the agent’s morphology, that is, its shape, limb articulation, as well as the position and density of sensors on its body surface. Despite its importance, the impact of morphology on behavior has not been systematically addressed. In this paper, we take inspiration from the human vision system, and demonstrate using a binocular active vision platform why sensor morphology in combination with other properties of the body, are essential conditions to achieve coordinated visual behavior (here, vergence). Specifically, to evaluate the effect of sensor morphology on behavior, we present an information-theoretic analysis quantifying the statistical regularities induced through sensorimotor interaction. Our results show that only for an adequate sensor morphology, vergence increases the amount of information structure in the sensorimotor loop.
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References
Lungarella, M., Sporns, O.: Mapping information flow in sensorimotor networks. PLoS Comp. Bio. 2(10), e14 (2006)
Pfeifer, R., Lungarella, M., Iida, F.: Self-organization, embodiment, and biologically inspired robotics. Science 318, 1088–1093 (2007)
Koerding, K.P., Wolpert, D.M.: Bayesian decision theory in sensorimotor control. Trends Cogn. Sci. 10, 319–326 (2006)
Thelen, E., Smith, L.: A dynamic systems approach to the development of cognition and action. MIT Press/Bradford (1994)
Schmidhuber, J.: Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes. In: Anticipatory Behavior in Adaptive Learning Systems, from Sensorimotor to Higher-level Cognitive Capabilities. LNCS (LNAI), pp. 48–76. Springer, Heidelberg (2009)
Oudeyer, P.-Y., Kaplan, F., Hafner, V.: Intrinsic Motivation Systems for Autonomous Mental Development. IEEE Trans. on Evol. Comp. 11(2), 265–286 (2007)
Barto, A., Singh, S., Chentanez, N.: Intrinsically motivated learning of hierarchical collections of skills. In: 3rd Int. Conf. Devel. Learn., pp. 112–119. IEEE Press, San Diego (2004)
Smith, P., Cowie, H., Blades, M.: Understanding children’s development. Blackwell, Malden (1998)
Tondel, G., Candy, T.: Human infants’ accommodation responses to dynamic stimuli. Investigative Ophthalmology & Visual Science 48(2), 949–956 (2007)
Aslin, R.N.: Development of binocular fixation in human infants. Journal of Exp. Child Psy. 23(1), 133–150 (1977)
Schreiber, T.: Measuring information transfer. Phys. Rev. Lett. 85, 461–464 (2000)
Beira, R., Lopes, M., Praça, M., Santos-Victor, J., Bernardino, A., Metta, G., Becchi, F., Saltarén, R.: Design of the Robot-Cub (iCub) Head. In: Conf. on Rob. and Auto., pp. 94–100. IEEE Press, Orlando (2006)
Birch, E., Petrig, B.: FPL and VEP Measures of Fusion, Stereopsis and Stereoacuity in Normal Infants. Vision Res. 36(9), 1321–1327 (1996)
Birch, E., Morale, S., Jeffrey, B., Oconnor, A., Fawcett, S.: Measurement of stereoacuity outcomes at ages 1 to 24 months: Randot stereocards. Journal of Ame. Asso. for Ped. Opht. and Stra. 9(1), 31–36 (2005)
Nothdurf, H.: Texture discrimination by cells in the cat lateral geniculate nucleus. Exp. Brain Res. 82, 48–66 (1990)
Itti, L., Koch, C.: Computational Modeling of Visual Attention. Nat. Rev. Neuro. 2(3), 194–203 (2001)
Wheatstone, C.: Contributions to the physiology of vision.-Part the First. On some remarkable, and hitherto unobserved, phenomena of binocular vision. Phil. Trans. of the Royal Soci. of London 128, 371–394 (1838)
Pearl, J.: Causality: Models, reasoning, and inference. Cambridge University Press, Cambridge (2000)
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Martinez, H., Sumioka, H., Lungarella, M., Pfeifer, R. (2010). On the Influence of Sensor Morphology on Vergence. In: Doncieux, S., Girard, B., Guillot, A., Hallam, J., Meyer, JA., Mouret, JB. (eds) From Animals to Animats 11. SAB 2010. Lecture Notes in Computer Science(), vol 6226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15193-4_14
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DOI: https://doi.org/10.1007/978-3-642-15193-4_14
Publisher Name: Springer, Berlin, Heidelberg
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