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Bootstrapping bilinear models of robotic sensorimotor cascades
Abstract We consider the bootstrapping problem, whi …
We consider the bootstrapping problem, which consists in learning a model of the agent's sensors and actuators starting from zero prior informa- tion, 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 proper- ties of learning and control are demonstrated with extensive simulations and by analytical arguments.
e simulations and by analytical arguments.  +
Authors Andrea Censi, Richard M Murray  +
ID 2010g  +
Source Workshop on the Algorithmic Foundations of Robotics (WAFR), 2010 (Submitted)  +
Tag cm10-wafr  +
Title Bootstrapping bilinear models of robotic sensorimotor cascades +
Type Preprint  +
Categories Papers
Modification date
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15 May 2016 06:16:18  +
URL
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http://www.cds.caltech.edu/~murray/preprints/cm10-wafr_s.pdf  +
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