| --- |
| 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. |
|
|
