File size: 2,788 Bytes
23eacd5 4625903 46f58dc 287360a 47ec1dc d92a001 288be3d db97a9b e02e902 71a05e7 e02e902 71a05e7 ad34114 71a05e7 3bc1755 71a05e7 4237e00 71a05e7 e02e902 4625903 71a05e7 3bc1755 71a05e7 6b8c191 e02e902 ad34114 3bc1755 288be3d |
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 |
---
license: mit
language:
- en
tags:
- code
- robotics
- manipulation
- modulus
- youngs
- youngs modulus
- compliance
- hardness
- tactile
- tactile sensing
- robotic manipulation
- gelsight
- shore
- shape
- material
---
GelSight Young's Modulus Dataset
==============
Dataset of tactile images collected over grasping common objects labelled with the objects' Young's Moduli. All images are collected using GelSight Wedges, both with and without displacement markers. Associated code is available on [GitHub](https://github.com/GelSight-lab/EstimateModulus/tree/main).
Pre-print is available on [arXiv](https://arxiv.org/abs/2406.15304).
Dataset Format
---------------
Each object is grasped a number of times, and each of these grasps is downsampled to 3 frames and shifted to create different data augmentations of the same grasp. Collected data is split into folders according to the following structure...
```
gelsight_youngs_modulus_dataset
βββ {object_name}
βββ metadata.json
βββ grasp={grasp_number}
βββ augmentation={augmentation_number}
βββ RGB.pkl
βββ depth.pkl
βββ RGB_markers.pkl
βββ depth_markers.pkl
βββ forces.pkl
βββ widths.pkl
βββ elastic_estimate.pkl
βββ hertz_estimate.pkl
```
In the OBJECT_NAME folder, metadata for each object is provided in a .json file, including the object's shape, material, Young's modulus, and Shore hardness.
```
metadata = {
'object_name': {object_name}, # [str]
'youngs_modulus': 0.0, # [Pa]
'material': '', # [str]
'shape': '', # [str]
'shore_00_hardness': None, # [/]
'shore_A_hardness': None, # [/]
'shore_D_hardness': None, # [/]
'used_in_training': True # [bool]
}
```
In the AUGMENTATION_NUMBER folder, data is provided in .pkl files. You will find the following named conventions...
- Tactile RGB images (3 images, without markers): `RGB.pkl`
- Tactile depth images (3 images, without markers): `depth.pkl`
- Tactile RGB images (3 images, with markers): `RGB_markers.pkl`
- Tactile depth images (3 images, with markers): `depth_markers.pkl`
- Sampled grasping contact forces: `forces.pkl`
- Sampled gripper widths: `widths.pkl`
- Elastic analytical model estimate: `elastic_estimate.pkl`
- Hertzian analytical model estimate: `hertz_estimate.pkl`
Dataset Diversity:
---------------
Shapes:
- Cylinder: 20.2%
- Rectangular: 15.3%
- Sphere: 11.5%
- Hexagonal: 2.1%
- Irregular: 50.9%
Materials:
- Rubber: 28.6%
- Metal: 25.1%
- Plastic: 24.0%
- Wood: 8.4%
- Foam: 6.3%
- Other: 7.6% |