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Replace RubiksCubeTask with 30-episode version

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  1. RubiksCubeTask/README.md +0 -89
  2. RubiksCubeTask/data/chunk-000/episode_000000.parquet +0 -3
  3. RubiksCubeTask/data/chunk-000/episode_000001.parquet +0 -3
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RubiksCubeTask/README.md DELETED
@@ -1,89 +0,0 @@
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- # RoboLab Motion-Planning GR00T Dataset
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-
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- This dataset was generated from RoboLab/Isaac Sim scripted Cartesian motion planning.
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- It is stored in the GR00T-flavored LeRobot v2 layout expected by NVIDIA Isaac-GR00T.
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-
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- ## Contents
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-
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- - Episodes: 100
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- - Frames: 20200
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- - FPS: 15
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- - Robot type metadata: `droid_abs_ik`
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- - State/action dimension: 8
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-
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- ## Tasks
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-
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- - `0`: Put the cube in the bowl
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-
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- ## Directory Layout
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-
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- ```text
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- meta/info.json
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- meta/modality.json
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- meta/tasks.jsonl
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- meta/episodes.jsonl
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- meta/stats.json
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- meta/relative_stats.json
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- data/chunk-000/episode_*.parquet
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- videos/chunk-000/<video_key>/episode_*.mp4
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- robolab_motionplanning_config.py
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- README.md
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- ```
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-
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- ## Data Format
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-
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- Each parquet row contains:
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-
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- - `observation.state`: float32 list `[x, y, z, qw, qx, qy, qz, gripper]`
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- - `action`: float32 list with the next end-effector target in the same format
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- - `timestamp`: seconds at 15 FPS
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- - `annotation.human.action.task_description`: integer index into `meta/tasks.jsonl`
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- - `task_index`, `episode_index`, `index`
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- - `next.reward`, `next.done`
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-
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- `meta/modality.json` splits state and action into:
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-
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- - `eef_position`: indices `[0:3]`
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- - `eef_quaternion_wxyz`: indices `[3:7]`
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- - `gripper`: indices `[7:8]`
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-
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- Video modalities:
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-
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- - `observation.images.front`
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- - `observation.images.wrist`
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-
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- ## Fine-Tuning GR00T
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-
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- Clone and install Isaac-GR00T following the official repository instructions:
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-
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- ```bash
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- git clone https://github.com/NVIDIA/Isaac-GR00T.git
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- cd Isaac-GR00T
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- ```
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-
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- Then fine-tune with this dataset path and the included modality config:
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-
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- ```bash
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- export NUM_GPUS=1
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- CUDA_VISIBLE_DEVICES=0 uv run python gr00t/experiment/launch_finetune.py --base-model-path nvidia/GR00T-N1.7-3B --dataset-path /path/to/this/dataset --embodiment-tag NEW_EMBODIMENT --modality-config-path /path/to/this/dataset/robolab_motionplanning_config.py --num-gpus $NUM_GPUS --output-dir /tmp/robolab_motionplanning_gr00t --save-total-limit 5 --save-steps 1000 --max-steps 2000 --global-batch-size 32 --dataloader-num-workers 4
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- ```
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-
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- For open-loop evaluation after training:
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-
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- ```bash
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- uv run python gr00t/eval/open_loop_eval.py --dataset-path /path/to/this/dataset --embodiment-tag NEW_EMBODIMENT --model-path /tmp/robolab_motionplanning_gr00t/checkpoint-2000 --traj-ids 0 --action-horizon 16 --steps 260 --modality-keys eef_position eef_quaternion_wxyz gripper
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- ```
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-
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- Notes:
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-
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- - This dataset stores Cartesian end-effector pose with quaternion orientation.
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- - The included GR00T config treats the three action slices as `NON_EEF` absolute vectors.
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- - For a production EEF-specific setup, convert quaternion orientation to a GR00T-supported EEF rotation format such as 6D rotation, then use the corresponding GR00T `ActionType.EEF` / action format.
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- - If you change the action horizon or modality config, regenerate GR00T statistics as described in the Isaac-GR00T data config guide.
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-
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- References:
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-
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- - https://github.com/NVIDIA/Isaac-GR00T
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- - https://github.com/NVIDIA/Isaac-GR00T/blob/main/getting_started/data_preparation.md
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- - https://github.com/NVIDIA/Isaac-GR00T/blob/main/getting_started/finetune_new_embodiment.md
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- - https://github.com/NVIDIA/Isaac-GR00T/blob/main/getting_started/data_config.md
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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