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Bootstrapping bilinear models of robotic sensorimotor cascades

Censi, Andrea and Murray, Richard M. (2011) Bootstrapping bilinear models of robotic sensorimotor cascades. In: 2011 IEEE International Conference on Robotics and Automation. IEEE , Piscataway, NJ, pp. 4318-4325. ISBN 9781612843865.

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We consider the bootstrapping problem, which consists in learning a model of the agent's sensors and actuators starting from zero prior information, and we take the problem of servoing as a cross-modal task to validate the learned models. We study the class of sensors with bilinear dynamics, for which the derivative of the observations is a bilinear form of the control commands and the observations themselves. This class of models is simple, yet general enough to represent the main phenomena of three representative sensors (field sampler, camera, and range-finder), apparently very different from one another. It also allows a bootstrapping algorithm based on Hebbian learning, and a simple bioplausible control strategy. The convergence properties of learning and control are demonstrated with extensive simulations and by analytical arguments.

Item Type:Book Section
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URLURL TypeDescription ItemTechnical Report
Censi, Andrea0000-0001-5162-0398
Murray, Richard M.0000-0002-5785-7481
Additional Information:© 2011 IEEE.
Record Number:CaltechAUTHORS:20190326-141247658
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Official Citation:A. Censi and R. M. Murray, "Bootstrapping bilinear models of robotic sensorimotor cascades," 2011 IEEE International Conference on Robotics and Automation, Shanghai, 2011, pp. 4318-4325. doi: 10.1109/ICRA.2011.5979844
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:94157
Deposited By: George Porter
Deposited On:27 Mar 2019 14:51
Last Modified:03 Oct 2019 21:01

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