DuoBench π0.5 (sim)

π0.5 policy for the bimanual FR3 Duo setup of DuoBench, trained on simulation data only for all 11 DuoBench sim tasks (one multi-task policy). Fine-tuned from lerobot/pi05_base (revision 9e55186) with LeRobot on the DuoBench dataset.

Project page: https://duobench.github.io/ DuoBench Code: https://github.com/RobotControlStack/duobench

Training

Data: 50 demonstrations per task from the <task>/sim folders of RobotControlStack/duobench (all tasks merged)
Inputs: head, left_wrist and right_wrist cameras (224x224) and the 16-D state (2 x 7 joints + 2 grippers); output: 16-D joint and gripper action
40,000 steps, batch size 16, learning rate 2.5e-5, action chunk 50, seed 1000
LeRobot commit c8ce413d; the full configuration is in train_config.json

Results

Success rate (%) in DuoBench simulation over 300 rollouts per task (seeds 0-299) with a Wilson 95% interval.

Task	Success	95% CI
ball_maze	5.0	[3.1, 8.1]
bin_sort	1.7	[0.7, 3.8]
block_balance	0.0	[0.0, 1.3]
carry_pot	26.0	[21.4, 31.2]
hinge_chest	26.7	[22.0, 31.9]
join_blocks	0.0	[0.0, 1.3]
pour_marbles	0.0	[0.0, 1.3]
spring_door	19.7	[15.6, 24.5]
transfer_cube	13.0	[9.7, 17.3]
transfer_gate	23.3	[18.9, 28.4]
transfer_reorient	1.3	[0.5, 3.4]
mean	10.6

Usage

# LeRobot at commit c8ce413d
from lerobot.policies.pi05.modeling_pi05 import PI05Policy

policy = PI05Policy.from_pretrained("RobotControlStack/duobench-pi05-sim")

See the DuoBench code for the simulation environments and evaluation.

Limitations

Trained on simulation data only; not meant for the real robot.
Loading needs a LeRobot version compatible with the commit above.

License

This model is a Model Derivative of Gemma (π0.5 is built on PaliGemma) and is distributed under the Gemma Terms of Use. Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms (see NOTICE). Use of this model is subject to the Gemma Prohibited Use Policy, which applies to every recipient and downstream user. The files in this repository are modified: they are the weights of lerobot/pi05_base fine-tuned on DuoBench simulation data.

Citation

If you find this model or DuoBench useful for your work, please consider citing it:

@misc{duobench,
  title={{DuoBench}: A Reproducible Benchmark for Bimanual Manipulation in Simulation and the Real World},
  author={Tobias J{\"u}lg and Seongjin Bien and Simon Hilber and Yannik Blei and Pierre Krack and Maximilian Li and Sven Parusel and Rudolf Lioutikov and Florian Walter and Wolfram Burgard},
  year={2026},
  url={https://arxiv.org/abs/2606.11901}
}