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» Robot introspection through learned hidden Markov models
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ICRA
2005
IEEE
150views Robotics» more  ICRA 2005»
14 years 1 months ago
Learning Sensor Network Topology through Monte Carlo Expectation Maximization
— We consider the problem of inferring sensor positions and a topological (i.e. qualitative) map of an environment given a set of cameras with non-overlapping fields of view. In...
Dimitri Marinakis, Gregory Dudek, David J. Fleet
ICRA
2003
IEEE
222views Robotics» more  ICRA 2003»
14 years 25 days ago
Path planning using learned constraints and preferences
— In this paper we present a novel method for robot path planning based on learning motion patterns. A motion pattern is defined as the path that results from applying a set of ...
Gregory Dudek, Saul Simhon
ICRA
2006
IEEE
149views Robotics» more  ICRA 2006»
14 years 1 months ago
On Learning the Statistical Representation of a Task and Generalizing it to Various Contexts
— This paper presents an architecture for solving generically the problem of extracting the constraints of a given task in a programming by demonstration framework and the problem...
Sylvain Calinon, Florent Guenter, Aude Billard
ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
14 years 2 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...
IROS
2008
IEEE
142views Robotics» more  IROS 2008»
14 years 1 months ago
Scaffolding on-line segmentation of full body human motion patterns
Abstract— This paper develops an approach for on-line segmentation of whole body human motion patterns during human motion observation and learning. A Hidden Markov Model is used...
Dana Kulic, Yoshihiko Nakamura