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» Control Model Learning for Whole-Body Mobile Manipulation
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IJON
2002
154views more  IJON 2002»
13 years 6 months ago
Nonlinear model predictive control of a cutting process
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...
Primoz Potocnik, Igor Grabec
TNN
1998
114views more  TNN 1998»
13 years 6 months ago
A new approach to artificial neural networks
: A novel approach to artificial neural networks is presented. The philosophy of this approach is based on two aspects: the design of task-specific networks, and a new neuron model...
Benedito Dias Baptista F. Filho, Eduardo Lobo Lust...
JIRS
2010
120views more  JIRS 2010»
13 years 5 months ago
Designing Decentralized Controllers for Distributed-Air-Jet MEMS-Based Micromanipulators by Reinforcement Learning
Distributed-air-jet MEMS-based systems have been proposed to manipulate small parts with high velocities and without any friction problems. The control of such distributed systems ...
Laëtitia Matignon, Guillaume J. Laurent, Nadi...
ROBOCUP
2004
Springer
147views Robotics» more  ROBOCUP 2004»
14 years 1 days ago
Learning to Drive and Simulate Autonomous Mobile Robots
We show how to apply learning methods to two robotics problems, namely the optimization of the on-board controller of an omnidirectional robot, and the derivation of a model of the...
Alexander Gloye, Cüneyt Göktekin, Anna E...
AR
2002
157views more  AR 2002»
13 years 6 months ago
Acquiring state from control dynamics to learn grasping policies for robot hands
Abstract--A prominent emerging theory of sensorimotor development in biological systems proposes that control knowledge is encoded in the dynamics of physical interaction with the ...
Roderic A. Grupen, Jefferson A. Coelho Jr.