Paper | Website | Documentation
FurnitureBench is the real-world furniture assembly benchmark, which aims at providing a reproducible and easy-to-use platform for long-horizon complex robotic manipulation.
It features
- Long-horizon complex manipulation tasks
- Standardized environment setup
- Python-based robot control stack
- FurnitureSim: a simulated environment
- Large-scale teleoperation dataset (200+ hours)
Please check out our website for more details.
We elaborate on the real-world environment setup guide and tutorials in our online document.
FurnitureSim is a simulator based on Isaac Gym. FurnitureSim works on Ubuntu and Python 3.8+. Please refer to Installing FurnitureSim and How to Use FurnitureSim for more details about FurnitureSim.
If you find FurnitureBench useful for your research, please cite this work:
@inproceedings{heo2023furniturebench,
title={FurnitureBench: Reproducible Real-World Benchmark for Long-Horizon Complex Manipulation},
author={Minho Heo and Youngwoon Lee and Doohyun Lee and Joseph J. Lim},
booktitle={Robotics: Science and Systems},
year={2023}
}
- Polymetis: https://github.com/facebookresearch/polymetis
- BC: Youngwoon's robot-learning repo.
- IQL: https://github.com/ikostrikov/implicit_q_learning
- R3M: https://github.com/facebookresearch/r3m
- VIP: https://github.com/facebookresearch/vip
- Factory: https://github.com/NVIDIA-Omniverse/IsaacGymEnvs/blob/main/docs/factory.md
- OSC controller references: https://github.com/StanfordVL/perls2 and https://github.com/ARISE-Initiative/robomimic and https://github.com/ARISE-Initiative/robosuite