Search is not available for this dataset
action listlengths 8 8 | observation.state listlengths 8 8 | observation.velocity listlengths 8 8 | episode_index int64 0 3k | frame_index int64 0 434 | index int64 0 210k | task_index int64 0 0 | timestamp float32 0 28.9 | next.done bool 2
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End of preview. Expand in Data Studio
This dataset was created using LeRobot.
Dataset Description
Successful BananaInBowl demonstrations collected from an RFCL-trained SAC policy in Isaac Lab (RoboLab), for behaviour-cloning research on strategy diversity.
Lane: metra-alpha — a sweep of the METRA intrinsic-reward scale alpha, with every
other axis held fixed (banana task, 50 demos, sf=0.5, z_dim=3, phi_space=full, z_unit=true).
Each dataset is one (difficulty level, alpha) cell. Difficulty here: soft.
Collection: deterministic rollouts (tanh(mean), no action noise), success episodes only.
Success is defined by the environment (K-step settle streak), so the hold segment is already
inside every trajectory. Initial states are drawn from the curated pose bank
(init_pose_source=dataset, train split) — the same distribution the policy was trained and
evaluated on.
Size: exactly 3000 episodes, physically subset from a larger merged dataset with a fixed
permutation. Do not use LeRobot's runtime episodes= argument to subsample further —
combined with delta_timestamps it collapses the action chunk and sets action_is_pad
everywhere, and it is silent (training loss goes down).
Video: H.264, constant frame rate (CFR-normalised after merge). Non-CFR merged video breaks the torchcodec backend used by pi0.5 fine-tuning.
Actions: absolute joint positions (7) + binary gripper (1). Delta conversion, if any, happens at training time — it is not baked in here.
Provenance: meta/provenance.json records the exact policy checkpoint, sampling mode and
initial-state sampler that produced this data.
Visualize
Open in the LeRobot dataset visualizer
- Homepage: [More Information Needed]
- Paper: [More Information Needed]
- License: apache-2.0
Dataset Structure
{
"codebase_version": "v3.0",
"robot_type": "unknown",
"total_episodes": 3000,
"total_frames": 210418,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 15,
"splits": {
"train": "0:3000"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
"features": {
"action": {
"dtype": "float32",
"shape": [
8
],
"names": {
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"j1",
"j2",
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]
},
"fps": 15
},
"observation.state": {
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"shape": [
8
],
"names": {
"motors": [
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"joint_2",
"joint_3",
"joint_4",
"joint_5",
"joint_6",
"joint_7"
]
},
"fps": 15
},
"observation.velocity": {
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"shape": [
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],
"names": null,
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},
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},
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},
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},
"timestamp": {
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},
"next.done": {
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"shape": [
1
],
"names": null,
"fps": 15
},
"observation.images.over_shoulder_left_camera": {
"dtype": "video",
"shape": [
270,
480,
3
],
"names": [
"height",
"width",
"channels"
],
"info": {
"video.height": 270,
"video.width": 480,
"video.codec": "avc1",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 15.0,
"video.channels": 3,
"has_audio": false
}
},
"observation.images.wrist_cam": {
"dtype": "video",
"shape": [
270,
480,
3
],
"names": [
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}
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