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Real-world robot navigation policies can achieve near-perfect sim-to-real transfer by directly learning the "interface" between velocity commands and observed feedback, bypassing complex actuator dynamics.
Achieving robot navigation policy training in under 20 seconds could revolutionize the deployment of DRL in robotics.