| # GraspGen: Scaling Simulated Grasping | |
| GraspGen is a large-scale simulated grasp dataset for multiple robot embodiments and grippers | |
| <img src="assets/cover.png" width="1000" height="250" title="readme1"> | |
| We release over 57 million grasps, computed for a subset of 8515 objects from the [Objaverse XL](https://objaverse.allenai.org/) (LVIS) dataset. We release grasps for three grippers: Franka Panda, the Robotiq-2f-140 industrial gripper, and suction. | |
| <img src="assets/montage2.png" width="1000" height="500" title="readme2"> | |
| ## Dataset Format | |
| The dataset is released in the [WebDataset](https://github.com/webdataset/webdataset) format. The folder structure of the dataset is as follows: | |
| ``` | |
| grasp_data/ | |
| franka/shard_{0-7}.tar | |
| robotiq2f140/shard_{0-7}.tar | |
| suction/shard_{0-7}.tar | |
| splits/ | |
| franka/{train/valid}_scenes.json | |
| robotiq2f140/{train/valid}_scenes.json | |
| suction/{train/valid}_scenes.json | |
| ``` | |
| We release test-train splits along with the grasp dataset. | |
| Each json file in the shard has the following data in a python dictionary. Note that `num_grasps=2000` per object. | |
| ``` | |
| ‘object’/ | |
| ‘scale’ # This is the scale of the asset | |
| ‘grasps’/ | |
| ‘object_in_gripper’ # boolean mask indicating grasp success, [num_grasps X 1] | |
| ‘transforms’ # Pose of the gripper in homogenous matrices, [num_grasps X 4 X 4] | |
| ``` | |
| ## Visualizing the dataset | |
| We have provided some standalone scripts for visualizing this dataset. See the header of the [visualize_dataset.py](scripts/visualize_dataset.py) for installation instructions | |
| Before running any of the visualization scripts, remember to start meshcat-server in a separate terminal: | |
| ``` shell | |
| meshcat-server | |
| ``` | |
| To visualize a single object from the dataset, alongside its grasps: | |
| ```shell | |
| cd scripts/ && python visualize_dataset.py --dataset_path /path/to/dataset --object_uuid {object_uuid} --object_file /path/to/mesh --gripper_name {choose from: franka, suction, robotiq2f140} | |
| ``` | |
| ## Objaverse dataset | |
| Please download the Objaverse XL (LVIS) objects separately. See the helper script [download_objaverse.py](scripts/download_objaverse.py) for instructions and usage. | |
| ## License | |
| License Copyright © 2025, NVIDIA Corporation & affiliates. All rights reserved. | |
| The dataset is released under a CC-BY 4.0 License. | |
| The visualization code is released under the [NVIDIA source code license](LICENSE). | |
| ## Contact | |
| Please reach out to [Adithya Murali](adithyamurali.com) ([email protected]) and [Clemens Eppner](https://clemense.github.io/) ([email protected]) for further enquiries | |