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Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware | HTML5

ar5iv.labs.arxiv.org · 13,397 words · saved by 1 readers

Fine manipulation tasks, such as threading cable ties or slotting a battery, are notoriously difficult for robots because they require precision, careful coordination of contact forces, and closed-loop visual feedback.…

Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware Tony Z. Zhao 1 Vikash Kumar 3 Sergey Levine 2 Chelsea Finn 1 1 Stanford University 2 UC Berkeley 3 Meta Abstract Fine manipulation tasks, such as threading cable ties or slotting a battery, are notoriously difficult for robots because they require precision, careful coordination of contact forces, and closed-loop visual feedback. Performing these tasks typically requires high-end robots, accurate sensors, or careful calibration, which can be expensive and difficult to set up. Can learning enable low-cost and imprecise hardware

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