File size: 2,901 Bytes
572efab d6f376d 572efab d6f376d 5610180 d6f376d bd70d67 d6f376d bd70d67 d6f376d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 |
---
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:
```text
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:
```python
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:
```bibtex
@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}
}
```
[](https://arxiv.org/abs/2308.08510)
|