Efficient movement representation by embedding Dynamic Movement Primitives in deep autoencoders
Authors:
- Nutan ChenNCNutan Chen
- Justin BayerJBJustin Bayer
- Sebastian UrbanSUSebastian Urban
- Patrick van der SmagtPSPatrick van der Smagt
- 1 November 2015
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 434-440
Abstract
No abstract availableThis publication has 9 references indexed in Scilit:
- Dynamical Movement Primitives: Learning Attractor Models for Motor BehaviorsNeural Computation, 2013
- Statistical dynamical systems for skills acquisition in humanoids2012
- Latent spaces for dynamic movement primitives2009
- Learning and generalization of motor skills by learning from demonstration2009
- Topologically-constrained latent variable models2008
- Extracting and composing robust features with denoising autoencoders2008
- Movement imitation with nonlinear dynamical systems in humanoid robots2003
- Constructive Incremental Learning from Only Local InformationNeural Computation, 1998
- The coordination of arm movements: an experimentally confirmed mathematical modelThe Journal of Neuroscience, 1985