Robot Learning by Demonstration with Local Gaussian Process Regression. In Proc. 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipeh, Taiwan, 2010. Learning from Demonstration using a Katana robotic manipulator. Note that in each demonstration the objects' positions change. Learning means to generalize from these training samples to an arbitrary new situation where all the objects can be located at different positions. In the reproduction, the manipulator's trajectory is computed based on the constraints extracted from the recorded demonstrations. Unlike in classical teach-in approaches, this method is able to deal with changing objects' positions.
Learning from Demonstration - Make Coffee
Experiment/Model Test
01.01.2010
27MB, 00:05:40:16
Audiovisuelles Material
Audiovisuelles Material
Englisch
Robot Learning from Demonstration by Averaging Trajectories - Making Coffee
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