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ESANN
1998
13 years 6 months ago
Lazy learning for control design
This paper presents two local methods for the control of discrete-time unknown nonlinear dynamical systems, when only a limited amount of input-output data is available. The modeli...
Gianluca Bontempi, Mauro Birattari, Hugues Bersini
ICRA
2002
IEEE
115views Robotics» more  ICRA 2002»
13 years 9 months ago
Parametric Primitives for Motor Representation and Control
The use of motor primitives for the generation of complex movements is a relatively new and interesting idea for dimensionality reduction in robot control. We propose a framework ...
R. Amit, Maja J. Mataric
ICCBR
2007
Springer
13 years 11 months ago
An Analysis of Case-Based Value Function Approximation by Approximating State Transition Graphs
We identify two fundamental points of utilizing CBR for an adaptive agent that tries to learn on the basis of trial and error without a model of its environment. The first link co...
Thomas Gabel, Martin Riedmiller
IROS
2006
IEEE
135views Robotics» more  IROS 2006»
13 years 10 months ago
Bio-inspired Model of Robot Adaptive Learning and Mapping
- In this paper we present a model designed on the basis of the neurophysiology of the rat hippocampus to control the navigation of a real robot. The model allows the robot to lear...
Alejandra Barrera Ramirez, Alfredo Weitzenfeld Rid...
ENGL
2008
153views more  ENGL 2008»
13 years 4 months ago
Neural Network NARMA Control of a Gyroscopic Inverted Pendulum
The objective herein is to demonstrate the feasibility of a real-time digital control of an inverted pendulum for modeling and control, with emphasis on nonlinear auto regressive m...
F. Chetouane, S. Darenfed