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CORR
2010
Springer
166views Education» more  CORR 2010»
13 years 5 months ago
A new closed-loop output error method for parameter identification of robot dynamics
Off-line robot dynamic identification methods are mostly based on the use of the inverse dynamic model, which is linear with respect to the dynamic parameters. This model is sample...
Maxime Gautier, Alexandre Janot, Pierre-Olivier Va...
PAMI
2008
140views more  PAMI 2008»
13 years 5 months ago
Simplifying Mixture Models Using the Unscented Transform
Mixture of Gaussians (MoG) model is a useful tool in statistical learning. In many learning processes that are based on mixture models, computational requirements are very demandin...
Jacob Goldberger, Hayit Greenspan, Jeremie Dreyfus...
TPDS
2010
260views more  TPDS 2010»
13 years 3 months ago
Real-Time Modeling of Wheel-Rail Contact Laws with System-On-Chip
—This paper presents the development and implementation of a multiprocessor system-on-chip solution for fast and real time simulations of complex and nonlinear wheel-rail contact...
Yongji Zhou, T. X. Mei, Steven Freear
BC
2000
95views more  BC 2000»
13 years 5 months ago
Cerebellar learning of accurate predictive control for fast-reaching movements
Long conduction delays in the nervous system prevent the accurate control of movements by feedback control alone. We present a new, biologically plausible cerebellar model to study...
Jacob Spoelstra, Nicolas Schweighofer, Michael A. ...
ICML
1994
IEEE
13 years 9 months ago
A Modular Q-Learning Architecture for Manipulator Task Decomposition
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
Chen K. Tham, Richard W. Prager