Iterative Reinforcement Learning Based Design of Dynamic Locomotion Skills for Cassie

Zhaoming Xie
Zhaoming Xie
Patrick Clary
Patrick Clary
Jeremy Dao
Jeremy Dao
Pedro Morais
Pedro Morais

arXiv: Robotics, 2019.

Cited by: 0|Views22
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Abstract:

Deep reinforcement learning (DRL) is a promising approach for developing legged locomotion skills. However, the iterative design process that is inevitable in practice is poorly supported by the default methodology. It is difficult to predict the outcomes of changes made to the reward functions, policy architectures, and the set of tasks ...More

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