metadata
license: mit
modalities:
- image
- tabular
configs:
- config_name: onland
data_files: onland/data_*.parquet
- config_name: underwater
data_files: underwater/data_*.parquet
dataset_info:
- config_name: onland
features:
- name: image
dtype: image
- name: fx
dtype: float32
- name: fy
dtype: float32
- name: fz
dtype: float32
- name: tx
dtype: float32
- name: ty
dtype: float32
- name: tz
dtype: float32
- name: object
dtype: string
- name: env
dtype: string
- config_name: underwater
features:
- name: image
dtype: image
- name: fx
dtype: float32
- name: fy
dtype: float32
- name: fz
dtype: float32
- name: tx
dtype: float32
- name: ty
dtype: float32
- name: tz
dtype: float32
- name: object
dtype: string
- name: env
dtype: string
size_categories:
- 10K<n<100K
FingerNet-Img-40k
This dataset contains about 40,000 samples of image and force data collected for soft robotic fingers interacting with various objects both on land and underwater.
Dataset Schema
The dataset is organized as follows:
fingernet-img-40k/
├── onland/
│ ├── data_0.parquet
│ ├── data_1.parquet
│ ├── data_2.parquet
│ └── ...
└── underwater/
├── data_0.parquet
├── data_1.parquet
├── data_2.parquet
└── ...
Each record in contains:
| Field | Type | Description |
|---|---|---|
image |
Image |
Image containing finger structure, 640x480 pixels |
Fx, Fy, Fz, Mx, My, Mz |
float32 |
6D force-torque data in N and Nmm |
object |
string |
Contacted object name |
env |
string |
Environment (onland / underwater) |
Usage
To read the dataset, you can use the following code:
from datasets import load_dataset
# Load the onland dataset
ds = load_dataset("asRobotics/magiclaw-touch-dataset", "onland")
print(ds[0])
# Load the underwater dataset
ds = load_dataset("asRobotics/magiclaw-touch-dataset", "underwater")
print(ds[0])
Citation
If you use this dataset in your research, please cite the following paper:
@article{guo2024autoencoding,
title={Autoencoding a Soft Touch to Learn Grasping from On-Land to Underwater},
author={Guo, Ning and Han, Xudong and Liu, Xiaobo and Zhong, Shuqiao and Zhou, Zhiyuan and Lin, Jian and Dai, Jiansheng and Wan, Fang and Song, Chaoyang},
journal={Advanced Intelligent Systems},
volume={6},
number={1},
pages={2300382},
year={2024},
publisher={Wiley Online Library},
doi = {10.1002/aisy.202300382}
}