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license: apache-2.0
task_categories:
- robotics
tags:
- robotics
- simulation
- isaac-sim
- franka
- discodemo
pretty_name: DiscoDemo raw states — StackCube
---
# DiscoDemo raw states: StackCube
Camera-free simulator state trajectories of the generated demonstrations for the **StackCube** task
("stack the red cube on the blue cube") on a real-to-sim Franka FR3 workcell in Isaac Sim, from
[DiscoDemo](https://davian-robotics.github.io/DiscoDemo/). Each file holds the 3,000 successful, safety-filtered
trajectories of one demonstration generator. Use them to analyze or re-render the demonstrations without
running the generators (object and end-effector trajectories, diversity and coverage analyses).
These are the trajectories of the generated datasets, in the same order: `traj_<i>` of `discodemo.h5` is episode `i`
of [`DAVIAN-Robotics/DiscoDemo-Stage2_GenData-StackCube`](https://huggingface.co/datasets/DAVIAN-Robotics/DiscoDemo-Stage2_GenData-StackCube),
and `traj_<i>` of `prfcl.h5` is episode `i` of
[`DAVIAN-Robotics/DiscoDemo-Stage2_GenData-StackCube-alpha0`](https://huggingface.co/datasets/DAVIAN-Robotics/DiscoDemo-Stage2_GenData-StackCube-alpha0).
| File | Generator | Trajectories | Steps (median / max) |
|---|---|---|---|
| `discodemo.h5` | DiscoDemo generator (diversity weight alpha = 0.3) | 3,000 | 165 / 539 |
| `prfcl.h5` | P-RFCL baseline (alpha = 0) | 3,000 | 117 / 278 |
## Format
One HDF5 file per generator, trajectories `traj_0` ... `traj_2999`, recorded at 20 Hz:
```
traj_<i>/
actions (T, 8) absolute FR3 joint position targets for joints 1-7 in the DROID
frame (joint 7 offset by -pi/4) and the binary gripper command (1 = close)
success (T+1,) task success predicate at each state
states/
robot/joint_pos (T+1, 9) 7 arm joints + 2 finger joints
robot/joint_vel (T+1, 9)
objects/
cube_blue/root_pose (T+1, 7) position (env frame) + quaternion (w, x, y, z)
cube_blue/root_vel (T+1, 6) linear + angular velocity (world frame)
cube_red/root_pose (T+1, 7) position (env frame) + quaternion (w, x, y, z)
cube_red/root_vel (T+1, 6) linear + angular velocity (world frame)
skill_z (3,) skill latent sampled for the episode (discodemo.h5 only)
```
The root attributes give the language instruction, the task name and the recording rate. End-effector poses can be recovered from `joint_pos` with forward kinematics of the FR3 model in
the code repository.
## Related resources
- Code (environments, generators, data pipeline, analysis): https://github.com/DAVIAN-Robotics/DiscoDemo
- Models and datasets: https://huggingface.co/collections/DAVIAN-Robotics/discodemo-6ac696e70d028fddf0c3dfeb
## Citation
```bibtex
@article{park2026discodemo,
title = {DiscoDemo: Discovering Efficient and Diverse Robot Demonstrations for Imitation Learning},
author = {Park, Minho and Kim, Kinam and Kim, Donghu and Lee, Byungkun and Hwang, Dongyoon and Shin, Yongjae and Hyung, Junha and Lee, Hojoon and Choo, Jaegul},
journal = {arXiv preprint},
year = {2026}
}
```
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