AnyGrasp SDK for grasp detection & tracking.
[arXiv] [project] [dataset] [graspnetAPI]
AnyGrasp cleaning fragments of a broken pot
AnyGrasp catching swimming robot fish
- Python 3.6/3.7/3.8/3.9
- PyTorch 1.7.1 with CUDA 11.0
- MinkowskiEngine v0.5.4
-
Follow MinkowskiEngine instructions to install Anaconda, cudatoolkit, Pytorch and MinkowskiEngine. Note that you need
export MAX_JOBS=2;beforepip installif you are running on an laptop due to this issue. If PyTorch reports a compatibility issue during program execution, you can re-install PyTorch via Pip instead of Anaconda. -
Install other requirements from Pip.
pip install -r requirements.txt- Install
pointnet2module.
cd pointnet2
python setup.py installDue to the ip issue, currently we can only release the SDK library file of AnyGrasp in a licensed manner. Please get the feature id of your machine and fill in the form to apply for the license. See license_registration/README.md for details. If you are interested in code implementation, you can refer to our baseline version of network.
Now you can run your code that uses AnyGrasp SDK. See grasp_detection and grasp_tracking for details.
Please cite these papers in your publications if it helps your research:
@article{fang2022anygrasp,
title={AnyGrasp: Robust and Efficient Grasp Perception in Spatial and Temporal Domains},
author = {Fang, Hao-Shu and Wang, Chenxi and Fang, Hongjie and Gou, Minghao and Liu, Jirong and Yan, Hengxu and Liu, Wenhai and Xie, Yichen and Lu, Cewu},
journal={arXiv preprint arXiv:2212.08333},
year={2022}
}
@inproceedings{fang2020graspnet,
title={Graspnet-1billion: A large-scale benchmark for general object grasping},
author={Fang, Hao-Shu and Wang, Chenxi and Gou, Minghao and Lu, Cewu},
booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
pages={11444--11453},
year={2020}
}
@inproceedings{wang2021graspness,
title={Graspness discovery in clutters for fast and accurate grasp detection},
author={Wang, Chenxi and Fang, Hao-Shu and Gou, Minghao and Fang, Hongjie and Gao, Jin and Lu, Cewu},
booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
pages={15964--15973},
year={2021}
}
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