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metadata
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. 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, and traj_<i> of prfcl.h5 is episode i of DAVIAN-Robotics/DiscoDemo-Stage2_GenData-StackCube-alpha0.

File Generator Trajectories Steps (median / max)
discodemo.h5 DiscoDemo generator (diversity weight alpha = 0.3) 3,000 163 / 598
prfcl.h5 P-RFCL baseline (alpha = 0) 3,000 155 / 259

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

Citation

@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}
}