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  2. README.md +119 -0
  3. dataset_summary.json +41 -0
  4. libero_10_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/meta/info.json +305 -0
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  45. libero_object_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/meta/info.json +305 -0
  46. libero_object_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/meta/modality.json +19 -0
  47. libero_object_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/meta/stats.json +919 -0
  48. libero_spatial_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/meta/info.json +305 -0
  49. libero_spatial_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/meta/modality.json +19 -0
  50. libero_spatial_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/meta/stats.json +919 -0
LICENSE ADDED
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ task_categories:
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+ - robotics
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+ tags:
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+ - LeRobot
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+ - LIBERO
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+ - robotics
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+ - vision-language-action
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+ - MiniCPM-RobotManip
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+ configs:
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+ - config_name: default
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+ data_files: "*/data/*/*.parquet"
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+ ---
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+
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+ # MiniCPM-RobotManip LIBERO
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+
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+ This dataset contains the four LIBERO suites converted to LeRobot v3 format
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+ for the MiniCPM-RobotManip LIBERO full-parameter fine-tuning example in
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+ [starVLA](https://github.com/starVLA/starVLA).
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+
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+ ## Dataset summary
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+
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+ | Suite | Episodes | Frames | Videos |
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+ |---|---:|---:|---:|
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+ | LIBERO-10 | 358 | 95,740 | 716 |
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+ | LIBERO-Goal | 405 | 48,131 | 810 |
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+ | LIBERO-Object | 450 | 66,294 | 900 |
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+ | LIBERO-Spatial | 423 | 51,707 | 846 |
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+ | **Total** | **1,636** | **261,872** | **3,272** |
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+
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+ - Format: LeRobot v3
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+ - Frequency: 20 Hz
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+ - Cameras: agent view and wrist view
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+ - Video resolution: 256 × 256
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+ - Action target: `observation.xvla_abs_ee6d`
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+ - Action target dimension: 10
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+
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+ ## EE6D target
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+
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+ `observation.xvla_abs_ee6d` contains an absolute single-arm target:
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+
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+ - `[0:3]`: xyz position
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+ - `[3:9]`: rotation6D
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+ - `[9]`: gripper closed (`0` = open, `1` = closed)
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+
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+ The starVLA MiniCPM-RobotManip recipe uses the current row as state and offsets
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+ 1–30 as the action chunk. It maps this 10-D vector to the left-arm `[7:17]`
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+ slot of MiniCPM-RobotManip's unified 80-D state/action space; other channels are
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+ masked out of the training loss.
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+
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+ Each suite includes `meta/modality.json` with the mapping expected by starVLA.
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+
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+ ### Legacy auxiliary column
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+
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+ The parquet files retain `actino.xvla_abs_ee6d`, a legacy auxiliary field from
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+ the original conversion pipeline. It is intentionally preserved for provenance
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+ and is not consumed by the published starVLA recipe. Use
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+ `observation.xvla_abs_ee6d` for both state and offset action targets.
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+
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+ ## Download
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+
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+ ```bash
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+ hf download openbmb/MiniCPM-RobotManip-LIBERO \
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+ --repo-type dataset \
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+ --local-dir playground/Datasets/LIBERO_EE6D
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+ ```
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+
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+ Expected top-level directories:
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+
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+ ```text
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+ libero_10_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/
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+ libero_goal_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/
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+ libero_object_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/
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+ libero_spatial_agentview_rot180_wrist_raw_lerobot_v30_xvla_abs6d/
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+ ```
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+
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+ ## Training with starVLA
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+
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+ ```bash
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+ VLM_PATH=openbmb/MiniCPM-RobotManip \
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+ LIBERO_EE6D_ROOT=playground/Datasets/LIBERO_EE6D \
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+ bash examples/modelExtensions/MiniCPM-RobotManip/train_files/run_libero_train.sh
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+ ```
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+
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+ The corresponding public base checkpoint is
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+ [`openbmb/MiniCPM-RobotManip`](https://huggingface.co/openbmb/MiniCPM-RobotManip).
88
+
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+ ## Source and processing
90
+
91
+ The demonstrations originate from the
92
+ [LIBERO benchmark](https://lifelong-robot-learning.github.io/LIBERO/). The four
93
+ suites were filtered, converted to LeRobot v3 at 20 Hz, and augmented with
94
+ absolute EE6D targets aligned to each parquet row and video frame. Original
95
+ observation and action fields are retained.
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+
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+ This release contains simulation demonstrations only. It does not contain
98
+ personal or human-subject data.
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+
100
+ ## License
101
+
102
+ Released under the Apache License 2.0. See `LICENSE`.
103
+
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+ ## Citation
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+
106
+ Please cite LIBERO and MiniCPM-Robot when using this dataset:
107
+
108
+ ```bibtex
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+ @inproceedings{liu2023libero,
110
+ title={LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning},
111
+ author={Liu, Bo and Zhu, Yifeng and Gao, Chongkai and Feng, Yihao and Liu, Qiang and Zhu, Yuke and Stone, Peter},
112
+ booktitle={Advances in Neural Information Processing Systems},
113
+ year={2023}
114
+ }
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+ ```
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+
117
+ For the current MiniCPM-Robot citation, see the
118
+ [MiniCPM-Robot project](https://github.com/OpenBMB/MiniCPM-Robot).
119
+
dataset_summary.json ADDED
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