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BulletArm is a benchmark and learning-environment for robotic manipulation.

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BulletArm is a benchmark and learning-environment for robotic manipulation. BulletArm provides a set of standardized benchmark tasks in simulation alongside a collection of baseline algorithms.

Table of Contents

  1. Announcements
  2. Installation
  3. Getting Started
  4. Contributions
  5. Cite

Announcements

June 24, 2022

  • Version 1.0.0 is live!

Install

  1. Clone this repo
    git clone https://github.com/ColinKohler/BulletArm.git
    cd BulletArm
    
  2. Install dependencies
    pip install -r requirements.txt 
    
  3. Install this package
    pip install .
    
    Or add to your PYTHONPATH
    export PYTHONPATH=/path/to/BulletArm/:$PYTHONPATH
    
  4. Run the block stacking demo
    python tutorials/block_stacking_demo.py
    

Getting Started

To get started with BulletArm please see the Getting Started section of the documentation.

Contributions

We hope that other researchers will help us extend this package by adding new tasks, robots, etc. Please see the Contributions section of the documentation for additional details.

Cite

The development of this package was part of the work done for our paper: BulletArm: An Open-Source Robotic Manipulation Benchmark and Learning Framework. Please cite this work if you use our code:

@misc{https://doi.org/10.48550/arxiv.2205.14292,
      doi = {10.48550/ARXIV.2205.14292},
      url = {https://arxiv.org/abs/2205.14292},
      author = {Wang, Dian and Kohler, Colin and Zhu, Xupeng and Jia, Mingxi and Platt, Robert},
      keywords = {Robotics (cs.RO), FOS: Computer and information sciences, FOS: Computer and information sciences},
      title = {BulletArm: An Open-Source Robotic Manipulation Benchmark and Learning Framework},
      publisher = {arXiv},
      year = {2022},
      copyright = {arXiv.org perpetual, non-exclusive license}
} 

Feel free to contact us.

License

BulletArm is distributed under GNU General Public License. See License.

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