Auto-conditioned Recurrent Mixture Density Networks for Complex Trajectory Generation
arXiv: Robotics, Volume abs/1810.00146, 2018.
Recent advancements in machine learning research have given rise to recurrent neural networks that are able to synthesize high-dimensional motion sequences over long time horizons. By leveraging these sequence learning techniques, we introduce a state transition model (STM) that is able to learn a variety of complex motion sequences in jo...More
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