Upload successful poses till round 2

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RobotPosterior_titan_tillR2/README.md

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+# merged — 多轮 Sim 成功抓取合并结果
+
+本目录下每个文件对应一个物体：`{obj_id}_robot_gt_merged.hdf5`。  
+只包含 **Isaac Sim 验证成功** 的抓取；无成功抓取的物体不会生成文件。
+
+---
+
+## 数据怎么来的
+
+流水线（详见仓库 `docs/grasp_collect_pipeline.md`）：
+
+```
+SAM3D mesh + scale
+    → tools/convert_obj_usd.py          → output/obj_usd/oakink/{obj}.usd
+    → tools/random_grasp_sampler.py    → candidates/round_XXXX/{obj}_grasp.hdf5
+    → sim/run_grasp_sim.py             → robot_gt/round_XXXX/{obj}_robot_gt.hdf5
+    → tools/merge_robot_gt.py          → merged/{obj}_robot_gt_merged.hdf5  （本目录）
+```
+
+说明：
+
+1. **候选**：`inference/grasp_pose.py` / `random_grasp_sampler` 在物体坐标系下生成多组抓取（raycast 等），写入 `candidates/round_XXXX/*_grasp.hdf5`。
+2. **Sim GT**：`run_grasp_sim.py` 在 Isaac Sim 中物理闭合夹爪，只把 **仿真成功** 的 pose 写入 `robot_gt/round_XXXX/*_robot_gt.hdf5` 的 `successful_grasps`；失败的候选在单轮文件里可能在 `candidate_results`，**合并时不会读**。
+3. **合并**：`merge_robot_gt.py`（或 `scripts/batch_grasp_collect.py` 每轮 sim 结束后自动调用）把该物体 **所有 round** 的 `successful_grasps` 拼到一个 HDF5。默认 **不去重**；若 batch 开启 `--merge-deduplicate`，会按位置/朝向去掉近似重复，并在文件属性里标记 `deduplicated=true`。
+
+默认 mesh 策略：**`--no-rotation`**（与 SAM3D 原始朝向一致）；`mesh_prerotation` 多为单位阵（`method=identity`）。
+
+---
+
+## 文件命名
+
+| 模式 | 示例 |
+|------|------|
+| `{obj_id}_robot_gt_merged.hdf5` | `A01001_robot_gt_merged.hdf5` |
+
+`obj_id` 为 OakInk 等数据集中的物体 ID（如 `A01001`、`O02001`）。
+
+---
+
+## HDF5 结构
+
+### 根（文件级 attributes）
+
+| 属性 | 类型 | 含义 |
+|------|------|------|
+| `obj_id` | str | 物体 ID |
+| `success` | bool | 是否有至少一条成功抓取 |
+| `n_successful` | int | 合并后的成功抓取条数 |
+| `n_before_merge` | int | 合并前各轮成功条数之和（去重前） |
+| `deduplicated` | bool | 合并时是否做了近重复剔除 |
+| `n_source_files` | int | 参与合并的 `robot_gt` 文件个数 |
+| `source_files` | str[] | 各轮 `*_robot_gt.hdf5` 的绝对路径（溯源用） |
+
+### 组 `successful_grasps/`
+
+- 属性 `count`：与 `n_successful` 相同。
+- 子组 `grasp_0`, `grasp_1`, …（按合并顺序编号，**不是**原始候选名）。
+
+每个 `grasp_i`：
+
+**Attributes**
+
+| 属性 | 含义 |
+|------|------|
+| `name` | 原始候选名（如 `raycast_3`） |
+| `score` | 生成阶段的抓取质量分 |
+| `gripper_width` | 标称夹爪开口（米） |
+| `approach_type` | 生成方式（如 `raycast`） |
+| `source_file` | 该条来自哪一轮 `robot_gt` HDF5 |
+| `has_contact_points` | Sim 是否写出接触点 |
+| `finger_width_actual` | Sim 实测指宽（仅 `has_contact_points=true` 时有意义） |
+
+**Datasets（坐标均在物体局部坐标系，单位：米）**
+
+| 数据集 | shape | 含义 |
+|--------|-------|------|
+| `grasp_point` | (3,) | 抓取中心 |
+| `rotation` | (3, 3) | 抓取姿态旋转矩阵；列 0 = 手指方向，列 2 = 接近方向 |
+| `approach_dir` | (3,) | `rotation` 第 3 列 |
+| `finger_dir` | (3,) | `rotation` 第 1 列 |
+| `contact_points_local` | (K, 3) | 指尖接触点（物体系；仅部分抓取有） |
+
+**子组 `mesh_prerotation/`**（与 USD / sampler 一致的 mesh 预旋转）
+
+| 成员 | 含义 |
+|------|------|
+| `euler_xyz_deg` (3,) | 预旋转欧拉角（度） |
+| `matrix` (3, 3) | 同上，旋转矩阵 |
+| attrs `dataset` | 数据集名（如 `oakink`） |
+| attrs `method` | 如 `identity` 或 `rotation.json` |
+| attrs `rotation_json_path` | 若来自 canonical rotation，对应 json 路径 |
+
+---
+
+## 读取示例
+
+```python
+import h5py
+
+with h5py.File("A01001_robot_gt_merged.hdf5", "r") as f:
+    obj_id = f.attrs["obj_id"]
+    n = f.attrs["n_successful"]
+    g0 = f["successful_grasps/grasp_0"]
+    point = g0["grasp_point"][:]
+    R = g0["rotation"][:]
+    name = g0.attrs["name"]
+```
+
+---
+
+## 相关脚本
+
+| 脚本 | 作用 |
+|------|------|
+| `tools/merge_robot_gt.py` | 手动合并多轮 `robot_gt` |
+| `scripts/batch_grasp_collect.py` | 全量 batch，自动写本目录 |
+| `tools/vis_robot_gt.py` | 可视化成功抓取 |