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» Affordance-based imitation learning in robots
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ICRA
2009
IEEE
125views Robotics» more  ICRA 2009»
14 years 2 months ago
Learning motor primitives for robotics
— The acquisition and self-improvement of novel motor skills is among the most important problems in robotics. Motor primitives offer one of the most promising frameworks for the...
Jens Kober, Jan Peters
ICPR
2004
IEEE
14 years 9 months ago
Periodic Nonlinear Principal Component Neural Networks for Humanoid Motion Segmentation, Generalization, and Generation
In an experiment with a soccer playing robot, periodic temporally-constrained nonlinear principal component neural networks (NLPCNNs) are shown to characterize humanoid motion eff...
Karl F. MacDorman, Rawichote Chalodhorn, Minoru As...
ICRA
2006
IEEE
149views Robotics» more  ICRA 2006»
14 years 1 months ago
On Learning the Statistical Representation of a Task and Generalizing it to Various Contexts
— This paper presents an architecture for solving generically the problem of extracting the constraints of a given task in a programming by demonstration framework and the problem...
Sylvain Calinon, Florent Guenter, Aude Billard
HRI
2006
ACM
14 years 1 months ago
Teaching robots by moulding behavior and scaffolding the environment
Programming robots to carry out useful tasks is both a complex and non-trivial exercise. A simple and intuitive method to allow humans to train and shape robot behaviour is clearl...
Joe Saunders, Chrystopher L. Nehaniv, Kerstin Daut...
IROS
2008
IEEE
111views Robotics» more  IROS 2008»
14 years 2 months ago
Learning perceptual coupling for motor primitives
—Dynamic system-based motor primitives [1] have enabled robots to learn complex tasks ranging from Tennisswings to locomotion. However, to date there have been only few extension...
Jens Kober, Betty J. Mohler, Jan Peters