Abstract
In this text we will present a novel solution for active perception built upon a probabilistic framework for multimodal perception of 3D structure and motion — the Bayesian Volumetric Map (BVM). This solution applies the notion of entropy to promote gaze control for active exploration of areas of high uncertainty on the BVM so as to dynamically build a spatial map of the environment storing the largest amount of information possible. Moreover, entropy-based exploration is shown to be an efficient behavioural strategy for active multimodal perception.
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References
Knill, D.C., Pouget, A.: The Bayesian brain: the role of uncertainty in neural coding and computation. TRENDS in Neurosciences 27(12), 712–719 (2004)
Elfes, A.: Using occupancy grids for mobile robot perception and navigation. IEEE Computer 22(6), 46–57 (1989)
Lebeltel, O.: Programmation Bayésienne des Robots. PhD thesis, Institut National Polytechnique de Grenoble, Grenoble, France (September 1999)
Tay, C., Mekhnacha, K., Chen, C., Yguel, M., Laugier, C.: An efficient formulation of the bayesian occupation filter for target tracking in dynamic environments. International Journal of Autonomous Vehicles (2007)
Pouget, A., Dayan, P., Zemel, R.: Information processing with population codes. Nature Reviews Neuroscience 1, 125–132 (2000)
Henkel, R.: A Simple and Fast Neural Network Approach to Stereovision. In: Jordan, M., Kearns, M., Solla, S. (eds.) Proceedings of the Conference on Neural Information Processing Systems — NIPS 1997, pp. 808–814. MIT Press, Cambridge (1998)
Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Revised second printing edn. Morgan Kaufmann Publishers, Inc. (Elsevier) (1988)
Yguel, M., Aycard, O., Laugier, C.: Efficient GPU-based Construction of Occupancy Grids Using several Laser Range-finders. International Journal of Autonomous Vehicles (2007)
Patterson, R.D., Allerhand, M.H., Giguère, C.: Time-domain modeling of peripheral auditory processing: A modular architecture and a software platform. J. AcoustS. Soc. Am, 1890–1894 (1995)
Pinho, C., Ferreira, J.F., Bessière, P., Dias, J.: A Bayesian Binaural System for 3D Sound-Source Localisation. In: International Conference on Cognitive Systems (CogSys 2008), University of Karlsruhe, Karlsruhe, Germany (April 2008)
Laurens, J., Droulez, J.: Bayesian processing of vestibular information. Biological Cybernetics (December 2006) (Published online: 5th December 2006)
Bajcsy, R.: Active perception vs passive perception. In: Third IEEE Workshop on Computer Vision, Bellair, Michigan, pp. 55–59 (1985)
Aloimonos, J., Weiss, I., Bandyopadhyay, A.: Active Vision. International Journal of Computer Vision 1, 333–356 (1987)
Rocha, R., Dias, J., Carvalho, A.: Cooperative Multi-Robot Systems: a study of Vision-based 3-D Mapping using Information Theory. Robotics and Autonomous Systems 53(3–4), 282–311 (2005)
Rocha, R., Dias, J., Carvalho, A.: Exploring information theory for vision-based volumetric mapping. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2005), Edmonton, Canada, August 2005, pp. 2409–2414 (2005)
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Ferreira, J.F., Pinho, C., Dias, J. (2008). Active Exploration Using Bayesian Models for Multimodal Perception. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_36
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DOI: https://doi.org/10.1007/978-3-540-69812-8_36
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