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» Learning to Control in Operational Space
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AAAI
2008
15 years 6 months ago
Exposing Parameters of a Trained Dynamic Model for Interactive Music Creation
As machine learning (ML) systems emerge in end-user applications, learning algorithms and classifiers will need to be robust to an increasingly unpredictable operating environment...
Dan Morris, Ian Simon, Sumit Basu
ICPR
2006
IEEE
16 years 5 months ago
Direct Mapping of Visual Input to Motor Torques
Most methods for visual control of robots formulate the robot command in joint or Cartesian space. To move the robot these commands are remapped to motor torques usually requiring...
Jeremiah J. Neubert, Nicola J. Ferrier
ICFP
2002
ACM
16 years 4 months ago
Final shift for call/cc: : direct implementation of shift and reset
We present a direct implementation of the shift and reset control operators in the Scheme 48 system. The new implementation improves upon the traditional technique of simulating s...
Martin Gasbichler, Michael Sperber
126
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CEC
2010
IEEE
15 years 5 months ago
Elitist Artificial Bee Colony for constrained real-parameter optimization
Abstract-- A novel algorithm to solve constrained realparameter optimization problems, based on the Artificial Bee Colony algorithm is introduced in this paper. The operators used ...
Efrén Mezura-Montes, Ramiro Ernesto Velez-K...
ICRA
2007
IEEE
155views Robotics» more  ICRA 2007»
15 years 10 months ago
Dogged Learning for Robots
— Ubiquitous robots need the ability to adapt their behaviour to the changing situations and demands they will encounter during their lifetimes. In particular, non-technical user...
Daniel H. Grollman, Odest Chadwicke Jenkins