• Corpus ID: 199405578

Combining learned skills and reinforcement learning for robotic manipulations

@article{Strudel2019CombiningLS,
  title={Combining learned skills and reinforcement learning for robotic manipulations},
  author={Robin Strudel and Alexander Pashevich and Igor Kalevatykh and Ivan Laptev and Josef Sivic and Cordelia Schmid},
  journal={ArXiv},
  year={2019},
  volume={abs/1908.00722}
}
Manipulation tasks such as preparing a meal or assembling furniture remain highly challenging for robotics and vision. The supervised approach of imitation learning can handle short tasks but suffers from compounding errors and the need of many demonstrations for longer and more complex tasks. Reinforcement learning (RL) can find solutions beyond demonstrations but requires tedious and task-specific reward engineering for multi-step problems. In this work we address the difficulties of both… 

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