RL-100: Toward Highly Reliable Real-World Robot Reinforcement Learning

from Embodied AI 101 · host Shaoqing Tan

RL-100 demonstrates highly reliable real-world RL manipulation achieving 900/900 success rates across 7 tasks with up to 250 consecutive trials without failure. It also shows strong robustness to disturbances and zero/few-shot adaptation capabilities.

Episode metadata supplied by the publisher feed · Published Jun 27, 2026

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RL-100: Toward Highly Reliable Real-World Robot Reinforcement Learning

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