Training of deep neural networks for the generation of dynamic movement primitives

DOI10.1016/J.NEUNET.2020.04.010zbMath1468.68187OpenAlexW3016483845WikidataQ93259138 ScholiaQ93259138MaRDI QIDQ1982413

Rok Pahič, Andrej Gams, Aleš Ude, Jun Morimoto, Barry Ridge

Publication date: 8 September 2021

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2020.04.010

zbMATH Keywords

robot skill learningdynamic movement primitivestraining of deep neural networks

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Artificial intelligence for robotics (68T40)

Uses Software

• darch
• MNIST
• PyTorch
• ImageNet
• Adam
• SegNet
• AlexNet

Cites Work

• Unnamed Item
• Multilayer feedforward networks are universal approximators
• Reducing the Dimensionality of Data with Neural Networks
• Dynamic programming algorithm optimization for spoken word recognition
• Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors
• Learning representations by back-propagating errors

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