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BC
2000
95views more  BC 2000»
13 years 7 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. ...
IROS
2006
IEEE
126views Robotics» more  IROS 2006»
14 years 1 months ago
A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks
Abstract— Tying suture knots is a time-consuming task performed frequently during Minimally Invasive Surgery (MIS). Automating this task could greatly reduce total surgery time f...
Hermann Georg Mayer, Faustino J. Gomez, Daan Wiers...
ICRA
1995
IEEE
151views Robotics» more  ICRA 1995»
13 years 11 months ago
Learning Impedance Control for Robotic Manipulators
—Learning control is a concept for controlling dynamic systems in an iterative manner. It arises from the recognition that robotic manipulators are usually used to perform repeti...
Chien-Chern Cheah, Danwei Wang
SBRN
2000
IEEE
13 years 11 months ago
Non-Linear Modelling and Chaotic Neural Networks
This paper proposes a simple methodology to construct an iterative neural network which mimics a given chaotic time series. The methodology uses the Gamma test to identify a suita...
Antonia J. Jones, Steve Margetts, Peter Durrant, A...
KES
1998
Springer
13 years 11 months ago
Intelligent control with the growing competitive linear local mapping neural network for robotic hand-eye coordination
Several intelligent features are embedded in the Growing Competitive Linear Local Mapping Neural Network. They result in an adaptive, fast-learning, very efficient control scheme, ...
Andrei Cimponeriu, Hubert Kihl