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license: apache-2.0
task_categories:
- robotics
language:
- en
tags:
- ace-ego-0
- robocasa
- gr1
- lerobot
- camera-space
- eef
---
# RoboCasa Camera-Space EEF (ACE-Ego-0)
LeRobot v2.0 demonstrations for the 24 GR1 RoboCasa TableTop tasks used by
[ACE-Ego-0](https://github.com/ACERobotics-VLA/ACE-Ego-0) SFT. Actions and states
are stored in the observation camera frame (end-effector position + rot6d, plus
gripper and waist).
This dataset does **not** include unused conversion caches (`experiments/`) or
legacy per-dataset index files. Training reads only the files listed below and
the shipped merged q99 statistics. The training code never recomputes norms.
## Layout
```text
<task>/
data/chunk-*/episode_*.parquet
videos/chunk-*/observation.images.ego_view/episode_*.mp4
meta/info.json
meta/modality.json
meta/episodes.jsonl
meta/stats_gr00t.json
meta/stats_gr00t_delta_q99_first_state.json
norm/absolute/{norm_manifest.json,merged_stats.json}
norm/delta/{norm_manifest.json,merged_stats.json}
```
Task directory names match `configs/robocasa24/datasets.yaml` in ACE-Ego-0, for
example `gr1_unified.PnPBottleToCabinetClose_GR1ArmsAndWaistFourierHands_1000`.
## Download
```bash
huggingface-cli download ACERobotics/Robocasa_Camera_Space_Eef \
--repo-type dataset \
--local-dir data/robocasa24
```
Point the public recipes at this folder:
```bash
python scripts/train.py \
--config configs/robocasa24/absolute_sft.yaml \
--data-root data/robocasa24 \
--norm-manifest data/robocasa24/norm/absolute/norm_manifest.json
```
Delta SFT uses `norm/delta/norm_manifest.json` and the delta recipe.
## Notes
- 24 tasks, about 5.82M frames, ego-view video at the source resolution.
- Absolute and Delta SFT share the same trajectories; only the shipped merged
statistics and the delta transform differ.
- Per-dataset `stats_gr00t*.json` files are completeness artifacts. Runtime q99
comes from `norm/{absolute,delta}/merged_stats.json`.
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