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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 crossmodal 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 rangefinder), 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  cm10wafr + 
Title  Bootstrapping bilinear models of robotic sensorimotor cascades + 
Type  Preprint + 
Categories  Papers 
Modification date This property is a special property in this wiki.

15 May 2016 06:16:18 + 
URL This property is a special property in this wiki.

http://www.cds.caltech.edu/~murray/preprints/cm10wafr_s.pdf + 
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Bootstrapping bilinear models of robotic sensorimotor cascades +  Title 
