Search is not available for this dataset
action listlengths 7 7 | observation.state listlengths 37 37 | observation.sim_state listlengths 45 45 | reward float32 0 1 | done bool 2
classes | success bool 2
classes | is_first bool 2
classes | is_last bool 2
classes | is_terminal bool 2
classes | source_demo_index int64 0 999 | observation.object listlengths 28 28 | observation.robot0_eef_pos listlengths 3 3 | observation.robot0_eef_quat listlengths 4 4 | observation.robot0_eef_vel_ang listlengths 3 3 | observation.robot0_eef_vel_lin listlengths 3 3 | observation.robot0_gripper_qpos listlengths 2 2 | observation.robot0_gripper_qvel listlengths 2 2 | observation.robot0_joint_pos listlengths 7 7 | observation.robot0_joint_pos_cos listlengths 7 7 | observation.robot0_joint_pos_sin listlengths 7 7 | observation.robot0_joint_vel listlengths 7 7 | timestamp float32 0 21.7 | frame_index int64 0 434 | episode_index int64 0 999 | index int64 0 359k | task_index int64 0 0 |
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End of preview. Expand in Data Studio
mimicgen_nut_assembly_d0_224x224
MimicGen NutAssembly_D0 demonstrations in LeRobot v3 format, with both cameras rendered at
224x224. Same pipeline and conventions as chomeed/mimicgen_coffee_d1_224x224, with one difference noted below: this task's reward is staged, so success is reward >= 1.0 rather than reward > 0.
| episodes | 1000 |
| frames | 358907 |
| fps | 20 |
| robot | Sawyer (OSC_POSE, control_freq 20) |
| cameras | agentview, eye_in_hand -- 224x224, AV1 crf 30 |
observation.state |
37 = 9 proprioceptive + 28 privileged object dims |
Provenance
Built from NVIDIA's released core/nut_assembly_d0.hdf5 (amandlek/mimicgen_datasets). That file
already contains every low-dim observation, but its images are only 84x84, so only the cameras
were recomputed: each frame's recorded states vector is written back into a live
NutAssembly_D0 and both views are re-rendered at 224x224. Every other column is copied verbatim
from the source hdf5, so this is a re-render, not a re-simulation, and no dynamics were replayed.
Fidelity check: re-rendering demo 0 at the source's own 84x84 and diffing against its stored images gives mean |difference| of 2.30 (agentview) and 3.27 (eye_in_hand) out of 255, versus 78.1 / 88.5 for a vertically flipped comparison. The small residual is expected -- the originals were rendered on a different OpenGL stack.
Schema
Follows the conventions of chomeed/mimicgen_coffee_d0_224x224:
observation.state(37) =concat(robot0_eef_pos, robot0_eef_quat, robot0_gripper_qpos, object), i.e. 9 proprioceptive dims followed by 28 privileged object dims. Slicing to the leading 9 gives a proprioception-only policy input.observation.sim_state(45) replays into a liveNutAssembly_D0.success == done == (reward >= 1.0). This task's reward is staged -- robosuite gives 0.5 for one nut seated and 1.0 for both -- so only the full reward counts as success.reward > 0would mark roughly half of every demo as successful.source_demo_index == episode_index-- the demo's index in the source hdf5.is_first/is_last/is_terminalmark only the first and last frame of an episode.
Column widths are task-specific: coffee carries a 57-dim object block plus *_rel_pod keys,
square a 17-dim block with no rel_* keys.
The robot is read from the source env_args: Sawyer.
License
cc-by-4.0, inherited from the MimicGen datasets this is derived from.
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