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Learning From a Steady Hand: A Weakly Supervised Agent for Robot Assistance under Microscopy
This paper rethinks steady-hand robotic manipulation by using a weakly supervised framework that fuses calibration-aware perception with admittance control. Unlike conventional automation that relies on labor-intensive 2D labeling, our framework leverages reusable warm-up trajectories to extract imp
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