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ECAI
2010
Springer
13 years 10 months ago
Variable Level-Of-Detail Motion Planning in Environments with Poorly Predictable Bodies
Motion planning in dynamic environments consists of the generation of a collision-free trajectory from an initial to a goal state. When the environment contains uncertainty, preven...
Stefan Zickler, Manuela M. Veloso
HYBRID
2007
Springer
14 years 4 months ago
Robust, Optimal Predictive Control of Jump Markov Linear Systems Using Particles
Hybrid discrete-continuous models, such as Jump Markov Linear Systems, are convenient tools for representing many real-world systems; in the case of fault detection, discrete jumps...
Lars Blackmore, Askar Bektassov, Masahiro Ono, Bri...
AUTOMATICA
2005
115views more  AUTOMATICA 2005»
13 years 10 months ago
Robust constrained predictive control using comparison model
This paper proposes a quadratic programming (QP) approach to robust model predictive control (MPC) for constrained linear systems having both model uncertainties and bounded distu...
Hiroaki Fukushima, Robert R. Bitmead
AIPS
2000
13 years 11 months ago
Representations of Decision-Theoretic Planning Tasks
Goal-directed Markov Decision Process models (GDMDPs) are good models for many decision-theoretic planning tasks. They have been used in conjunction with two different reward stru...
Sven Koenig, Yaxin Liu
JETAI
2002
69views more  JETAI 2002»
13 years 9 months ago
The interaction of representations and planning objectives for decision-theoretic planning tasks
We study decision-theoretic planning or reinforcement learning in the presence of traps such as steep slopes for outdoor robots or staircases for indoor robots. In this case, achi...
Sven Koenig, Yaxin Liu