Robot Inference Library (robInfLib) provides various demos of using Kernelized Movement Primitives, which is maintained by Dr. Yanlong Huang (University of Leeds)Part of the codes are provided by Dr. João Silvério, Dr. Fares J. Abu-Dakka and Dr. Sylvain Calinon,which have been acknowledged in the corresponding files.

DEMOS ILLUSTRATIONS

REFERENCE

[1] KMP: learning and adaptation

@InProceedings{Huang19ICRA_1,   Title = {Non-parametric Imitation Learning of Robot Motor Skills},   Author = {Huang, Y. and Rozo, L. and Silv\'erio, J. and Caldwell, D. G.},   Booktitle = {Proc. {IEEE} International Conference on Robotics and Automation ({ICRA})},   Year = {2019},   Address = {Montreal, Canada},   Month = {May},   Pages = {5266--5272}}

[2] KMP: learning, adaptation, superposition and extrapolaton.

@Article{Huang19IJRR,  Title = {Kernelized Movement Primitives},  Author = {Huang, Y. and Rozo, L. and Silv\'erio, J. and Caldwell, D. G.},  Journal = {International Journal of Robotics Research},  Year = {2019},  Volume={38},  Number={7},  Pages = {833--852},}

[3] KMP orientation: learning and adaptation

@InProceedings{Huang19ICRA_2,   Title = {Generalized Orientation Learning in Robot Task Space},   Author = {Huang, Y. and Abu-Dakka, F. and Silv\'erio, J. and Caldwell, D. G.},   Booktitle = {Proc. {IEEE} International Conference on Robotics and Automation ({ICRA})},　　　　   Year = {2019},   Address = {Montreal, Canada},   Month = {May},   Pages = {2531--2537} }

[4] Uncertainty-aware KMP: uncertainty/covariance prediction and adaptation

@InProceedings{silverio2019uncertainty,  Title = {Uncertainty-Aware Imitation Learning using Kernelized Movement Primitives},  Author = {Silv\'erio, J. and Huang, Y. and Abu-Dakka, Fares J and Rozo, L. and  Caldwell, D. G.},  Booktitle = {Proc. {IEEE/RSJ} International Conference on Intelligent Robots and Systems ({IROS})},  Year = {2019},  Pages={90--97}}