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workflows/simbox/tools/grasp/README.md

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+# Grasp Pose Generation and Visualization
+
+## Installation
+
+```bash
+pip install torch numba numpy "open3d>=0.16.0" tqdm
+```
+
+## Part 1: Grasp Pose Generation
+
+Grasp poses are generated based on mesh geometry and force closure analysis. The annotation pipeline follows the process from [AnyGrasp SDK](https://github.com/graspnet/anygrasp_sdk) and supports GPU acceleration. The output includes both dense annotations and filtered sparse annotations.
+
+We use the **sparse annotation results** for grasping. The output is an `N x 17` array with the following structure:
+
+```
+[score, width, height, depth, view_angles (9), points (3), obj_ids (1)]
+```
+
+| Field | Dimensions | Description |
+|-------|------------|-------------|
+| `score` | 1 | Grasp quality score (0.1-1.0, lower is better) |
+| `width` | 1 | Grasp width |
+| `height` | 1 | Grasp height |
+| `depth` | 1 | Grasp depth |
+| `view_angles` | 9 | Can be reshaped to a 3x3 rotation matrix |
+| `points` | 3 | 3D position of grasp center |
+| `obj_ids` | 1 | Object identifier |
+
+The definitions of `width`, `height`, and `depth` follow the conventions in the GraspNet and AnyGrasp papers. The `view_angles` combined with `points` and `depth` form the transformation `T_obj_tcp`. The gripper frame definition is consistent with the GraspNet API:
+
+<p align="center">
+  <img src="graspnet_def.png" alt="GraspNet Gripper Frame Definition" style="width: 400px;">
+</p>
+
+**Note:** The generated grasp poses require coordinate transformation before use. Refer to `pose_post_process_fn()` in `template_robot.py` for details.
+
+**References:**
+- [AnyGrasp SDK](https://github.com/graspnet/anygrasp_sdk)
+- [GraspNet API](https://github.com/graspnet/graspnetAPI)
+
+### Usage
+
+```bash
+python gen_sparse_label.py --obj_path xxx.obj --unit mm --sparse_num 3000 --max_widths 0.1
+```
+
+**Arguments:**
+- `--obj_path`: Path to the object mesh file (.obj format)
+- `--unit`: Unit of the mesh, either `mm` (millimeters) or `m` (meters)
+- `--sparse_num`: Number of sparse grasp poses to filter (recommended: 3000)
+- `--max_widths`: Maximum gripper width (default: 0.1)
+
+## Part 2: Grasp Pose Visualization
+
+Visualize generated grasp poses on the object mesh.
+
+### Usage
+
+```bash
+python vis_grasp.py --obj_path xxx.obj --N 100 --unit mm
+```
+
+**Arguments:**
+- `--obj_path`: Path to the object mesh file (.obj format)
+- `-N`: Number of grasp poses to visualize
+- `--unit`: Unit of the mesh, either `mm` (millimeters) or `m` (meters)