Skip to content
/ rpmart Public

RPMArt: Towards Robust Perception and Manipulation for Articulated Objects

License

Notifications You must be signed in to change notification settings

R-PMArt/rpmart

Folders and files

NameName
Last commit message
Last commit date

Latest commit

7ba0826 Β· Feb 14, 2025

History

4 Commits
Oct 1, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Oct 1, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Feb 14, 2025
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024
Jul 6, 2024

Repository files navigation

RPMArt

Website Paper IROS

teaser

Official implementation for the paper RPMArt: Towards Robust Perception and Manipulation for Articulated Objects, accepted by IROS 2024.

For more information, please visit our project website.


πŸ›  Installation

πŸ’» Server-side

  1. Clone this repo.

    git clone [email protected]:R-PMArt/rpmart.git
    cd rpmart
  2. Create a Conda environment.

    conda create -n rpmart python=3.8
    conda activate rpmart
  3. Install PyTorch.

    pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 --extra-index-url https://download.pytorch.org/whl/cu113
  4. Install pytorch-gradual-warmup-lr.

    cd deps
    git clone [email protected]:ildoonet/pytorch-gradual-warmup-lr.git
    cd pytorch-gradual-warmup-lr
    pip install .
    cd ../..
  5. Install MinkowskiEngine.

    conda install openblas-devel -c anaconda
    export CUDA_HOME=/usr/local/cuda
    pip install ninja
    cd deps
    git clone [email protected]:NVIDIA/MinkowskiEngine.git
    cd MinkowskiEngine
    pip install -U . --no-deps --install-option="--blas_include_dirs=${CONDA_PREFIX}/include" --install-option="--blas=openblas"
    cd ../..
  6. Install CuPy.

    pip install cupy-cuda11x
  7. Install special SAPIEN.

    pip install http://download.cs.stanford.edu/orion/where2act/where2act_sapien_wheels/sapien-0.8.0.dev0-cp38-cp38-manylinux2014_x86_64.whl
  8. Install AnyGrasp.

    pip install cvxopt munch graspnetAPI
    # follow AnyGrasp to use the licenses and weights and binary codes
  9. Install other dependencies.

    pip install -r requirements.txt
  10. Build shot.

    # you may need first install pybind11 and pcl
    cd src_shot
    mkdir build
    cd build
    cmake ..
    make
    cd ../..

🦾 Robot-side

  1. Make sure rt-linux is enabled for Franka Emika Panda.

    uname -a
  2. Install frankx for robot and pyrealsense2 for camera.

    pip install frankx pyrealsense2
  3. Install paramiko for connecting with server.

    pip install paramiko

πŸƒβ€β™‚οΈ Run

  1. Train or download RoArtNet.

    bash scripts/train.sh
  2. Test RoArtNet.

    bash scripts/test.sh
  3. Evaluate RPMArt.

    bash scripts/eval_roartnet.sh
  4. Test RoArtNet on RealArt-6.

    bash scripts/test_real.sh
  5. Evaluate RPMArt in the real world.

    # server side
    bash scripts/real_service.sh
    
    # robot side
    python real_eval.py

πŸ™ Acknowledgement

  • Our simulation environment is adapted from VAT-Mart.
  • Our voting module is adapted from CPPF and CPPF++.

✍ Citation

If you find our work useful, please consider citing:

@inproceedings{wang2024rpmart,
  title={RPMArt: Towards Robust Perception and Manipulation for Articulated Objects},
  author={Wang, Junbo and Liu, Wenhai and Yu, Qiaojun and You, Yang and Liu, Liu and Wang, Weiming and Lu, Cewu},
  booktitle={2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2024},
  pages={7270-7277},
  doi={10.1109/IROS58592.2024.10802368}
}

πŸ“ƒ License

This repository is released under the MIT license.

About

RPMArt: Towards Robust Perception and Manipulation for Articulated Objects

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published