---
license: bsd-3-clause
task_categories:
- robotics
tags:
- fingernet
- asfinger
size_categories:
- 100K<n<1M
---

# FingerNet-100K

This dataset contains 100K samples of data for FingerNet, generated by finite element simulations.

## Dataset Schema

There are two subsets in this dataset:

- **finger**: Contains 100,000 samples of typical asFinger.
- **finger_surf**: Contains 100,000 samples of asFinger with a contact surface.

Each sample in this dataset contains three components:

- **motion** (`List[float]`, shape = [6])  
  The 6D motion of the finger, including the translation (dx, dy, dz) in `mm`, and rotation (rx, ry, rz) in `rad`.

- **force** (`List[float]`, shape = [6])  
  The 6D force and torque on the bottom surface of the finger, corresponding to (fx, fy, fz, tx, ty, tz) in `N` and `Nmm`.

- **nodes** (`List[float]`, shape = [Nx3])  
  The 3D displacement of N surface nodes of the finger, and each node `i` is represented as `[node_i_dx, node_i_dy, node_i_dz]` in `mm`.

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("asRobotics/fingernet-100k")

# Access the 'finger' subset
finger_data = dataset['finger']

```

## Citation

If you use this model in your research, please cite the following papers:

```bibtex
@article{guo2024proprioceptive,
  title={Proprioceptive State Estimation for Amphibious Tactile Sensing},
  author={Guo, Ning and Han, Xudong and Zhong, Shuqiao and Zhou, Zhiyuan and Lin, Jian and Dai, Jian S and Wan, Fang and Song, Chaoyang},
  journal={IEEE Transactions on Robotics},
  volume={40},
  pages={4684-4698},
  year={2024},
  publisher={IEEE},
  doi={10.1109/TRO.2024.3463509}
}
```

```bibtex
@article{liu2024proprioceptive,
  title={Proprioceptive learning with soft polyhedral networks},
  author={Liu, Xiaobo and Han, Xudong and Hong, Wei and Wan, Fang and Song, Chaoyang},
  journal={The International Journal of Robotics Research},
  volume = {43},
  number = {12},
  pages = {1916-1935},
  year = {2024},
  publisher={SAGE Publications Sage UK: London, England},
  doi = {10.1177/02783649241238765}
}
```

```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},
    pages={2500444},
    year={2025},
    publisher={Wiley Online Library},
    doi={10.1002/aisy.202500444}
}
```