Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations

Robotics: Science and Systems, 2018.

Cited by: 184|Bibtex|Views131|DOI:https://doi.org/10.15607/rss.2018.xiv.049
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Dexterous multi-fingered hands are extremely versatile and provide a generic way to perform multiple tasks in human-centric environments. However, effectively controlling them remains challenging due to their high dimensionality and large number of potential contacts. Deep reinforcement learning (DRL) provides a model-agnostic approach to...More

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