LeRobot (v2 / v2.1)
SignIQ exportsHugging Face's PyTorch-native robot dataset format. Parquet for low-dim, MP4 for video, JSONL/JSON metadata. Modern default for VLA work.
File structure
meta/info.json
meta/episodes.jsonl
meta/tasks.jsonl
meta/stats.json
data/chunk-XXX/episode_XXX.parquet
videos/chunk-XXX/<camera>/episode_XXX.mp4
Required fields
- ●observation.images.<camera>
- ●observation.state
- ●action
- ●timestamp
- ●frame_index
- ●episode_index
Optional fields
task (language instruction) · next.reward · next.done · annotation.<custom>
Action representation
Per-dataset; documented in meta/info.json features
Best for
openpi / GR00T / OpenVLA / LeRobot fine-tuning and PyTorch pipelines
Used by
LeRobot, openpi, GR00T (with modality.json), many OXE mirrors
SignIQ export
Yes — shipped natively
GR00T-LeRobot
SignIQ exportsLeRobot v2 with an additional meta/modality.json that maps state, action, and video keys to GR00T's policy expectations. Required for Isaac-GR00T fine-tuning.
File structure
All LeRobot v2 files
meta/modality.json (state.<part>, action.<part>, video.<view>)
meta/embodiment.json
Required fields
- ●modality.state.<body_part>
- ●modality.action.<body_part>
- ●modality.video.<camera>
- ●embodiment tag
Optional fields
language · reward · subtask spans
Action representation
Per body part; GR00T handles chunking and tokenization internally
Best for
GR00T N1 / N1.7 fine-tuning on humanoid and bimanual platforms
Used by
NVIDIA GR00T, Isaac Lab post-training
SignIQ export
Yes — shipped natively
HDF5 (ALOHA / robomimic / ACT)
SignIQ exportsHierarchical binary format with embedded multi-camera image stacks and joint trajectories. The native format for ACT, robomimic, and many bimanual recipes.
File structure
/observations/images/<camera>
/observations/qpos
/observations/qvel
/action
/episode_metadata
Required fields
- ●observations.qpos
- ●action
- ●episode metadata
Optional fields
observations.images.<camera> · observations.qvel · observations.gripper · language_instruction
Action representation
Joint targets or action chunks; embedded shape/length per dataset
Best for
ACT, Diffusion Policy, robomimic baselines, ALOHA tooling
Used by
ACT, robomimic, Diffusion Policy, ALOHA scripts
SignIQ export
Yes — shipped natively
MCAP / ROS 2
SignIQ exportsROS-native log container. Best for replay, debugging, and end-to-end systems work where the full message bus matters.
File structure
<bag>.mcap (channel-keyed messages)
<bag>.metadata.yaml
Required fields
- ●/tf and /tf_static
- ●/joint_states
- ●/<camera>/image_raw
Optional fields
/wrench · /audio · /diagnostics · /<custom>
Action representation
Joint commands or twist/wrench messages on a control topic
Best for
Robotics infra teams, replay/visualization, ROS-first stacks
Used by
Foxglove, rosbag2, ROS 2 native pipelines
SignIQ export
Yes — shipped natively
RLDS / TFRecord
RLDS is the canonical format behind Open X-Embodiment. JAX/TF pipelines (Octo, OpenVLA) consume it directly.
File structure
*.tfrecord shards
features.json
dataset_info.json
Required fields
- ●steps[].observation
- ●steps[].action
- ●steps[].is_terminal
- ●steps[].language_instruction (optional)
Optional fields
episode_metadata · discount · reward
Action representation
Most VLA work uses 7D EEF delta + gripper
Best for
OXE/RT-X, OpenVLA, Octo, JAX/TF pretraining
Used by
Open X-Embodiment, OpenVLA, Octo, RT-X
robomimic
SignIQ exportsCurated HDF5 layout with proficient-human, multi-human, and machine-generated splits. Strong baselines and clean evaluation.
File structure
data/demo_<i>/obs/<key>
data/demo_<i>/actions
data/demo_<i>/dones
mask/train, mask/valid
Optional fields
rewards · next_obs · states (sim)
Action representation
Joint deltas or absolute targets per dataset config
Best for
Offline imitation learning, BC/diffusion baselines, ablations
Used by
robomimic, robosuite, diffusion policy baselines
SignIQ export
Yes — shipped natively