This repo contains a easy to use and modular implementation of the benchmark environment for grasping in cluttered environments introduces by Breyer et. al [1]. Note that we incoorperate slight modifications as done by Huang et. al [2] to allow the network to skip and acquire a new viewpoint.
This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.
Installing the benchmark environment
# Clone the repo
# Install the requirements
pip install -r requirements.txt
# Install the package
pip install -e .
# Download the datasets and checkpoints
python scripts/download_data.py
ICG-Net
# Evaluate in packed scene
python scripts/test_icgnet.py --scene packed --object-set packed/test
# Evaluate in pile scene
python scripts/test_icgnet.py --scene pile --object-set pile/testEdge-Grasp Network
# Evaluate in packed scene
python scripts/test_edge.py --method edge-vn --scene packed --object-set packed/test
# Evaluate in pile scene
python scripts/test_edge.py --method edge-vn --scene pile --object-set pile/testVN-Edge-Grasp Network
# Evaluate in packed scene
python scripts/test_edge.py --method edge-vn --scene packed --object-set packed/test
# Evaluate in pile scene
python scripts/test_edge.py --method edge-vn --scene pile --object-set pile/testGIGA Network
# Evaluate in packed scene
python scripts/test_giga.py --scene packed --object-set packed/test
# Evaluate in pile scene
python scripts/test_giga.py --scene pile --object-set pile/testWill be updated soon.
Distributed under the BSD-2 License. See LICENSE.txt for more information.
If you use this code in your research, please cite the following paper:
@article{zurbrugg2024icgnet,
title={ICGNet: A Unified Approach for Instance-Centric Grasping},
author={Zurbr{\"u}gg, Ren{\'e} and Liu, Yifan and Engelmann, Francis and Kumar, Suryansh and Hutter, Marco and Patil, Vaishakh and Yu, Fisher},
journal={arXiv preprint arXiv:2401.09939},
year={2024}
}
Also consider citing the original work by Breyer et. al that introduced the benchmark environment:
@inproceedings{breyer2020volumetric,
title={Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in Clutter},
author={Breyer, Michel and Chung, Jen Jen and Ott, Lionel and Roland, Siegwart and Juan, Nieto},
booktitle={Conference on Robot Learning},
year={2020},
}
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