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+ # Robotic Manipulation Models for Four Tasks
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+ [[Project Page]](https://data-scaling-laws.github.io/)
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+ [[Paper]](https://data-scaling-laws.github.io/paper.pdf)
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+ [[Code]](https://github.com/Fanqi-Lin/Data-Scaling-Laws)
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+ This repository contains four models for the manipulation tasks described in the paper "Data Scaling Laws in Imitation Learning for Robotic Manipulation".
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+ The tasks include:
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+ + Arrange Mouse
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+ + Fold Towel
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+ + Pour Water
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+ + Unplug Charger
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+ For each task, we release a policy trained on data collected from 32 unique environment-object pairs, with 50 demonstrations per environment. These policies have been shown to generalize effectively to novel environments and objects.
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+ For details on how to use these models, please refer to our [code](https://github.com/Fanqi-Lin/Data-Scaling-Laws).