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ESANN
2001

A divide-and-conquer learning architecture for predicting unknown motion

9 years 3 months ago
A divide-and-conquer learning architecture for predicting unknown motion
Time varying environments or model selection problems lead to crucial dilemmas in identification and control science. In this paper, we propose a modular prediction scheme consisting in a mixture of expert architecture. Several Kalman filters are forced to adapt their dynamics and parameters to different parts of the whole dynamics of the system. The performances of this modular learning scheme are evaluated on a visual servoing problem: motion prediction of an object in a 3-D space for pursuing it with a 3 degree-of-freedom robot manipulator.
Patrice Wira, Jean-Philippe Urban, Julien Gresser
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2001
Where ESANN
Authors Patrice Wira, Jean-Philippe Urban, Julien Gresser
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