---
license: apache-2.0
pipeline_tag: object-detection
tags:
- graspgen
- grasp-generation
- point-cloud
- robotics
- IB-Robot
- ascend
- torch
- edge-deployment
---

# Model Card for GraspGen (IB-Robot)

GraspGen (Generative Grasp Sampler with Diffusion Denoiser + Discriminator) for point-cloud-based robotic grasp generation, packaged for the [IB-Robot](https://atomgit.com/openeuler/IB_Robot) framework with two deployments sharing one contract.

## Deployments

| deployment | backend | artifacts | notes |
|---|---|---|---|
| `ascend_310p` | Ascend ACL (Ascend310P1) | 8 OM modules | board-side pipeline (generator/discriminator split graph, device links) |
| `torch_cuda` | PyTorch CUDA | — (weights in `assets/`) | host-side debugging and evaluation |

Both deployments share the same `tensor_model/graspgen/generate_grasps` contract
(`observation.object_points [-1,3] -> grasp.poses [-1,4,4] + grasp.confidence [-1]`).

## Weights provenance

- `assets/generator_checkpoint.pth` = NVlabs/GraspGen `checkpoints/graspgen_robotiq_2f_140_gen.pth`
  (sha256 `fe8497108e39d8fc50be06cd7df22a2f680e0495e713d24c3104616f291e00dd`)
- `assets/discriminator_checkpoint.pth` = `graspgen_robotiq_2f_140_dis.pth`
- The 310P OM modules were converted from the same checkpoint — both deployments
  are weight-identical (sha pinned in `assets/adapter.json`).

## Repository Structure

- `inference_manifest.json` — deployment routing (schema v3)
- `assets/adapter.json` — algorithm contract, runtime parameters, checkpoint digests
- `assets/graspgen_config.yml` — upstream omegaconf config (robotiq_2f_140)
- `assets/generator_checkpoint.pth` / `assets/discriminator_checkpoint.pth` — Torch weights
- `artifacts/ascend/ascend_310p/*.om` — compiled 8-role pipeline

## Usage

Host (CUDA, requires the `grasp_gen` package with pointnet2_ops):

```python
from inference_manifest import load_inference_manifest
validated = load_inference_manifest("models/grasp", "torch_cuda")
# driven via manipulation_service.graspgen_wrapper (inference_backend="local_cuda")
```

Board (Ascend 310P): select the `ascend_310p` deployment through the IB-Robot
unified inference runtime.

## License

Code and packaging: Apache-2.0. GraspGen model weights follow the
NVlabs/GraspGen upstream license (NVIDIA Source Code License) — check
compatibility before redistribution.