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README.md

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 ---
 license: mit
+task_categories:
+- robotics
+tags:
+- prosoro
+modalities:
+  - tabular
+configs:
+  - config_name: cylinder
+    data_files: data/cylinder/data_*.parquet
+  - config_name: dome
+    data_files: data/dome/data_*.parquet
+  - config_name: neck
+    data_files: data/neck/data_*.parquet
+  - config_name: octagonal_prism
+    data_files: data/octagonal_prism/data_*.parquet
+  - config_name: origami
+    data_files: data/origami/data_*.parquet
+  - config_name: quadrangular_prism
+    data_files: data/quadrangular_prism/data_*.parquet
+dataset_info:
+  - config_name: cylinder
+    features:
+    - name: motion
+      sequence: float64
+    - name: force
+      sequence: float64
+    - name: nodes
+      sequence:
+        sequence: float64
+  - config_name: dome
+    features:
+    - name: motion
+      sequence: float64
+    - name: force
+      sequence: float64
+    - name: nodes
+      sequence:
+        sequence: float64
+  - config_name: neck
+    features:
+    - name: motion
+      sequence: float64
+    - name: force
+      sequence: float64
+    - name: nodes
+      sequence:
+        sequence: float64
+  - config_name: octagonal_prism
+    features:
+    - name: motion
+      sequence: float64
+    - name: force
+      sequence: float64
+    - name: nodes
+      sequence:
+        sequence: float64
+  - config_name: origami
+    features:
+    - name: motion
+      sequence: float64
+    - name: force
+      sequence: float64
+    - name: nodes
+      sequence:
+        sequence: float64
+  - config_name: quadrangular_prism
+    features:
+    - name: motion
+      sequence: float64
+    - name: force
+      sequence: float64
+    - name: nodes
+      sequence:
+        sequence: float64
+size_categories:
+- 100K<n<1M
 ---
+
+# ProSoRo-100K
+
+This dataset contains 100K samples of data for six different soft robotic structures: cylinder, dome, neck, octagonal prism, origami, and quadrangular prism. They were generated by finite element simulations, and used for training [ProSoRo-MVAE](https://huggingface.co/asRobotics/prosoro-mvae).
+
+## Dataset Schema
+
+There are six subsets in this dataset, one for each soft robotic structure. Each subset contains the following features:
+
+| **Field Name** | **Type** | **Shape** | **Description** |
+|----------------|----------|-----------|-----------------|
+| `motion`      | `List[float64]` | `[6]`     | The 6D motion of the ProSoRo, including translation (dx, dy, dz) and rotation (rx, ry, rz) in `mm` and `rad`. |
+| `force`       | `List[float64]` | `[6]`     | The 6D force and torque on the bottom surface of the ProSoRo, corresponding to (fx, fy, fz, tx, ty, tz) in `N` and `Nmm`. |
+| `nodes`       | `List[List[float64]]` | `[N,3]` | The 3D displacement of N surface nodes of the ProSoRo, where each node is represented as `[dx, dy, dz]` in `mm`. |
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("asRobotics/prosoro-100k")
+
+# Access the cylinder subset
+for sample in dataset['cylinder']:
+    print(sample['motion'], sample['force'], sample['nodes'])
+```
+
+## Citation
+
+If you use this model in your research, please cite the following paper:
+
+```bibtex
+@article{han2025anchoring,
+    title={Anchoring Morphological Representations Unlocks Latent Proprioception in Soft Robots},
+    author={Han, Xudong and Guo, Ning and Xu, Ronghan and Wan, Fang and Song, Chaoyang},
+    journal={Advanced Intelligent Systems},
+    volume={0},
+    pages={0-0},
+    year={2025}
+}
+```

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