README.md

metadata

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 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

<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

huggingface-cli download ACERobotics/Robocasa_Camera_Space_Eef \
  --repo-type dataset \
  --local-dir data/robocasa24

Point the public recipes at this folder:

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.