Abstract: Bipedal robots have achieved remarkable locomotion capabilities through reinforcement learning (RL), yet their real-world deployment remains hindered by the sim-to-real gap—dynamics ...
Reinforcement Learning (RL) has shown its remarkable and generalizable capability in legged locomotion through sim-to-real transfer. However, while adaptive methods like domain randomization are ...
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