Documentation | Paper | License

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.

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

• Version 1.0.0 is live!

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
   

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

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.

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.

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