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arXiv · 2404.17668

Precise Object Placement Using Force-Torque Feedback

Osher Lerner·Zachary Tam·Michael Equi
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Abstract

Precise object manipulation and placement is a common problem for household robots, surgery robots, and robots working on in-situ construction. Prior work using computer vision, depth sensors, and reinforcement learning lacks the ability to reactively recover from planning errors, execution errors, or sensor noise. This work introduces a method that uses force-torque sensing to robustly place objects in stable poses, even in adversarial environments. On 46 trials, our method finds success rates of 100% for basic stacking, and 17% for cases requiring adjustment.

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Osher Lerner, Zachary Tam, Michael Equi. 2024-04-26. Precise Object Placement Using Force-Torque Feedback. https://arxiv.org/abs/2404.17668

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