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.


    Access

    Go to TIB AV-Portal


    Export, share and cite



    Title :

    Learning from Demonstration - Make Coffee


    Subtitle :

    Experiment/Model Test




    Publication date :

    2010-01-01


    Size :

    27MB, 00:05:40:16



    Type of media :

    Audio-visual


    Type of material :

    Audio-visual


    Language :

    English





    Learning from Demonstration

    Ertel, Wolfgang | TIB AV-Portal | 2010

    Free access

    Learning from Demonstration - Stacking objects by color (demonstration)

    Ertel, Wolfgang | TIB AV-Portal | 2011

    Free access

    Learning from Demonstration - Sorting objects by shape (demonstration)

    Ertel, Wolfgang | TIB AV-Portal | 2011

    Free access

    High-Level Learning from Demonstration

    Ertel, Wolfgang | TIB AV-Portal | 2015

    Free access


    Preview

    Preview Image