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Rapid On-Robot Learning for Dynamic Manipulation Skills: Robot Juggling

arXiv · AI, language, vision and robotics · article · Aug 27, 2026 · UTC

We present an online learning framework that enables a bimanual robot to acquire diverse juggling patterns directly on physical hardware within minutes, even with a significant sim2real gap. One of the most important lessons from this work is that a model, even when far from reality, can be extremely useful for learning. This motivates a central philosophy of our approach: learning should build upon the robot's current knowledge rather than replace it. Our regularized memory-based learning puts this principle into practice by learning a local model from accumulated experience while retaining t

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