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Bootstrapping sensorimotor cascades: a group-theoretic perspective

Censi, Andrea and Murray, Richard M. (2011) Bootstrapping sensorimotor cascades: a group-theoretic perspective. In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE International Conference on Intelligent Robots and Systems. IEEE , Piscataway, NJ, pp. 2056-2063. ISBN 978-1-61284-454-1.

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The bootstrapping problem consists in designing agents that learn a model of themselves and the world, and utilize it to achieve useful tasks. It is different from other learning problems as the agent starts with uninterpreted observations and commands, and with minimal prior information about the world. in this paper, we give a mathematical formalization of this aspect of the problem. We argue that the vague constrain of having “no prior information” can be recast as a precise algebraic condition on the agent: that its behavior is invariant to particular classes of nuisances on the world, which we show can be well represented by actions of groups (diffeomorphisms, permutations, linear transformations) on observations and commans. We then introduce the class of bilinear gradient dynamics sensors (BGDS) as a candidate for learning generic robotic sensorimotor cascades. We show how framing the problem as rejection of group nuisances allows a compact and modular analysis of typical preprocessing stages, such as learning the topology of the sensors. We demonstrate learning and using such models on real-word range-finder and camera date from publicly available datasets.

Item Type:Book Section
Related URLs:
URLURL TypeDescription DOIArticle
Censi, Andrea0000-0001-5162-0398
Murray, Richard M.0000-0002-5785-7481
Additional Information:© 2011 IEEE. Date of Current Version: 05 December 2011.
Series Name:IEEE International Conference on Intelligent Robots and Systems
Record Number:CaltechAUTHORS:20120406-140547979
Persistent URL:
Official Citation:Censi, Andrea; Murray, Richard M.; , "Bootstrapping sensorimotor cascades: A group-theoretic perspective," Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on , vol., no., pp.2056-2063, 25-30 Sept. 2011 doi: 10.1109/IROS.2011.6095151 URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:30020
Deposited By: Ruth Sustaita
Deposited On:06 Apr 2012 21:21
Last Modified:03 Oct 2019 03:46

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