Robotics

Echo: Scaling Visual Reinforcement Learning with Off-policy Experience

Echo targets the compute costs of visual reinforcement learning with off-policy experience

Scaling visual reinforcement learning (RL) with GPU-accelerated simulation is computationally expensive due to rendering and visual-policy inference costs.

ArXiv CS.RO

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5h ago2 min

ArXiv CS.RO2026-10-30

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Visual reinforcement learning can demand substantial compute because simulation must render scenes and run visual policies. Echo’s focus on off-policy experience points to a way of addressing the challenge of scaling this kind of training.

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