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» Probabilistic inference for structured planning in robotics
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JAIR
2010
145views more  JAIR 2010»
13 years 3 months ago
Planning with Noisy Probabilistic Relational Rules
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
Tobias Lang, Marc Toussaint
ISRR
2005
Springer
99views Robotics» more  ISRR 2005»
13 years 10 months ago
On the Probabilistic Foundations of Probabilistic Roadmap Planning
Why is probabilistic roadmap (PRM) planning probabilistic? How does the probability measure used for sampling a robot’s configuration space affect the performance of a PRM plan...
David Hsu, Jean-Claude Latombe, Hanna Kurniawati
IROS
2008
IEEE
144views Robotics» more  IROS 2008»
13 years 11 months ago
Learning nonparametric policies by imitation
— A long cherished goal in artificial intelligence has been the ability to endow a robot with the capacity to learn and generalize skills from watching a human teacher. Such an ...
David B. Grimes, Rajesh P. N. Rao
RAS
2010
164views more  RAS 2010»
13 years 3 months ago
Towards performing everyday manipulation activities
This article investigates fundamental issues in scaling autonomous personal robots towards open-ended sets of everyday manipulation tasks which involve high complexity and vague j...
Michael Beetz, Dominik Jain, Lorenz Mösenlech...
ICML
2009
IEEE
14 years 5 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint