Auto-conditioned Recurrent Mixture Density Networks for Learning Generalizable Robot Skills

Hejia Zhang
Hejia Zhang
Eric Heiden
Eric Heiden
Stefanos Nikolaidis
Stefanos Nikolaidis

international conference on robotics and automation, 2019.

Cited by: 1|Bibtex|Views22|

Abstract:

Personal robots assisting humans must perform complex manipulation tasks that are typically difficult to specify in traditional motion planning pipelines, where multiple objectives must be met and the high-level context be taken into consideration. Learning from demonstration (LfD) provides a promising way to learn these kind of complex...More

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