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datasets: |
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- Fanqi-Lin/Processed-Task-Dataset |
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metrics: |
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- accuracy |
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pipeline_tag: robotics |
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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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[[Processed Dataset]](https://huggingface.co/datasets/Fanqi-Lin/Processed-Task-Dataset) |
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[[Raw GoPro Videos]](https://huggingface.co/datasets/Fanqi-Lin/GoPro-Raw-Videos) |
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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). |
