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[R] Huge Step Forward in Legged Robotics from ETH
Control policies learned via RL are starting to work in the real world!
Typically policies learned via simulation tend to transfer poorly to the real world (the so-called sim2real gap), so I'm curious to dig into this work to see how they overcame this limitation.
From just watching the video and guessing, it would make sense if noising the belief state (rnn(h,concat(proprio,extero)) + \eps ~ Noise) and learning to condition proprioceptive attention on the belief uncertainty is enough. Very …!-->