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» POMDP Planning for Robust Robot Control
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ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
13 years 11 months ago
Bayesian reinforcement learning in continuous POMDPs with application to robot navigation
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...
JAIR
2002
120views more  JAIR 2002»
13 years 5 months ago
Learning Geometrically-Constrained Hidden Markov Models for Robot Navigation: Bridging the Topological-Geometrical Gap
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Hagit Shatkay, Leslie Pack Kaelbling
UAI
2003
13 years 6 months ago
Policy-contingent abstraction for robust robot control
ontingent abstraction for robust robot control Joelle Pineau, Geoff Gordon and Sebastian Thrun School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 This pape...
Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun
JAIR
2006
160views more  JAIR 2006»
13 years 5 months ago
Anytime Point-Based Approximations for Large POMDPs
The Partially Observable Markov Decision Process has long been recognized as a rich framework for real-world planning and control problems, especially in robotics. However exact s...
Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun
ICRA
2005
IEEE
129views Robotics» more  ICRA 2005»
13 years 11 months ago
Dynamic Programming in Reduced Dimensional Spaces: Dynamic Planning For Robust Biped Locomotion
— We explore the use of computational optimal control techniques for automated construction of policies in complex dynamic environments. Our implementation of dynamic programming...
Mike Stilman, Christopher G. Atkeson, James Kuffne...