Empirical comparison shows a clear sim-to-real gap in reset-free RL for agile driving: TD-MPC2 outperforms the MPPI baseline in the real world while SAC excels in simulation, and residual learning benefits simulation but does not transfer.
Reset-free reinforcement learning via multi- task learning: Learning dexterous manipulation behaviors without human intervention,
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Reset-Free Reinforcement Learning for Real-World Agile Driving: An Empirical Study
Empirical comparison shows a clear sim-to-real gap in reset-free RL for agile driving: TD-MPC2 outperforms the MPPI baseline in the real world while SAC excels in simulation, and residual learning benefits simulation but does not transfer.