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Towards Reinforcement Learning for Space Robotics: Fast Training and Reliable Real-World Transfer
This work demonstrates the use of a fast simulation-based training framework to learn control policies using reinforcement learning. The hardware requirements are minimal and the simulation-learned policies transfer reliably to the real world. With this setup, we show that a quadruped robot can lear
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