README.md

---
license: apache-2.0
task_categories:
  - robotics
tags:
  - LeRobot
  - ur10
  - robotiq
  - tactile
  - depth
  - cluttered-grasping
  - imitation-learning
configs:
  - config_name: default
    data_files: data/*/*.parquet
---

# Cluttered Grasp (UR10 + Robotiq 2F-140 + tactile + depth)

Real-robot teleop demonstrations of cluttered grasping. Episodes are gated on
`gripper_tcp` height in `base_link` (record while low, pause while high), time-synced
to the RealSense **RGB master @ 30 Hz**, then converted to
[LeRobot](https://github.com/huggingface/lerobot) format.

| | |
|---|---|
| **Robot** | UR10 + Robotiq 2F-140 (`ur10_robotiq_2f140`) |
| **FPS** | **30** (RGB master timeline) |
| **Episodes / frames** | See `meta/info.json` (`total_episodes`, `total_frames`) |
| **Codebase** | LeRobot dataset v3.0 |
| **Task** | `cluttered grasping` |

## Sensors & resolutions

| Stream | Capture (ROS) | Dataset feature | Shape (H×W×C) | Notes |
|--------|---------------|-----------------|---------------|--------|
| Center RGB | RealSense color `1280×720@30` JPEG (`color/image_raw`) | `observation.images.center_cam` | **720×1280×3** | 16:9 color optical frame |
| Depth | RealSense depth module **`848×480@30` (W×H)**, **`/camera/camera/depth/image_rect_raw`** — **not** align-to-color | `observation.images.center_cam_depth` | **480×848×1** (uint16 mm, `video12`) | Unaligned native depth grid; **not** registered to RGB pixels |
| Tactile L | Fingertip cam JPEG (~90 Hz capture, hold-last to RGB) | `observation.images.tactile_L` | **240×320×3** | 4:3 |
| Tactile R | same | `observation.images.tactile_R` | **240×320×3** | 4:3 |

- **Master clock:** compressed RGB frames — one dataset row per RGB stamp (~30 Hz).
- **Sync:** nearest-neighbor within ~50 ms, then hold-last for depth/tactile/proprio.
- **Depth (logged & exported):** native D4xx depth at **848×480** from `depth/image_rect_raw` into bags → zarr `center_cam_depth` → LeRobot. Unit **millimetres** (uint16). **Not** the 1280×720 `aligned_depth_to_color` stream (that is used at runtime for ContactGraspNet only).
- **Depth vs RGB:** depth rows are time-synced to RGB but **not** pixel-aligned — fuse with extrinsics / reprojection, not naive `(u,v)` overlay on `center_cam`.
- Depth export for this dataset: **12-bit `gray12le` HEVC** (`video12`), log-quantized over **0.2–1.0 m**.

## Dataset structure

```text
cluttered_grasping/
├── meta/
│   ├── info.json          # schema, fps, totals, video codec info
│   ├── stats.json         # per-feature normalization stats
│   ├── tasks.parquet      # task prompts
│   └── episodes/          # per-episode metadata
├── data/
│   └── chunk-*/file-*.parquet   # state, action, indices
└── videos/
    ├── observation.images.center_cam/chunk-*/file-*.mp4        # AV1 1280×720 (W×H)
    ├── observation.images.center_cam_depth/chunk-*/file-*.mp4  # HEVC gray12le unaligned depth 848×480 (W×H)
    ├── observation.images.tactile_L/chunk-*/file-*.mp4         # AV1, 320×240
    └── observation.images.tactile_R/chunk-*/file-*.mp4
```

### Features (per frame)

| Key | Type | Shape | Description |
|-----|------|-------|-------------|
| `observation.state` | float32 | (8,) | `eef_x/y/z`, `eef_qx/qy/qz/qw` (xyzw), **measured** `gripper` at observation `t` |
| `action` | float32 | (7,) | `delta_x/y/z`, `delta_roll/pitch/yaw` (world, `t→t+1`) + gripper **mode** `{-1,0,+1}` at `t` (last frame dropped) |
| `observation.joint_state` | float32 | (7,) | `joint_0..5`, measured `gripper` at `t` (gripper redundant with `observation.state`) |
| `observation.joint_action` | float32 | (7,) | `joint_0..5` absolute at `t+1` + gripper mode at `t` (same mode as `action`) |
| `observation.gripper_setpoint` | float32 | (1,) | Absolute finger_joint command at `t` (under-the-hood; not the discrete action) |
| `observation.cgn_grasp_pose` | float32 | (7,) | Constant CGN TCP target in `base_link` (xyz + quat xyzw); broadcast every frame |
| `episode_state` | int64 | (1,) | Trajectory phase: `0` reach (home→CGN pose), `1` grasp_lift |
| `intervention` | int64 | (1,) | Sticky `1` after human teleop starts this episode (else `0`) |
| `grasp_state` | int64 | (1,) | Exclusive grasp phase at observation `t`: `0` no_contact, `1` contact, `2` closure, `3` lift, `4` success |
| `next.success` | float32 | (1,) | `1.0` on the **last exported frame** when terminal `grasp_state` is `success`; else `0` |
| `next.done` | float32 | (1,) | `1.0` on the **last exported frame** of every episode; else `0` |
| `observation.images.center_cam` | video (AV1) | 720×1280×3 | Scene RealSense RGB (1280×720 capture) |
| `observation.images.center_cam_depth` | video (HEVC gray12le) | 480×848×1 | Unaligned native depth **848×480** capture (H×W×C storage); mm; `is_depth_map` |
| `observation.images.tactile_L` | video (AV1) | 240×320×3 | Left fingertip tactile (`/tactile1`) |
| `observation.images.tactile_R` | video (AV1) | 240×320×3 | Right fingertip tactile (`/tactile2`) |
| `timestamp` | float32 | (1,) | Time within episode (s) |
| `frame_index` / `episode_index` / `index` / `task_index` | int64 | (1,) | LeRobot indices |

`observation.state` EE pose is `gripper_tcp` in `base_link`.  
`action` pose delta: `delta_xyz = pos[t+1]-pos[t]`; `delta_rpy = euler_xyz(R[t+1] @ R[t].T)` (world/fixed-frame).  
Gripper on both action channels is discrete **mode** (`-1` open, `0` hold, `+1` close), not absolute position. Under the hood teleop/CGN ramp a setpoint (logged in zarr as `gripper_setpoint`) with the same controller.  
Wrist force/torque is **not** exported to LeRobot (still present in upstream zarr if needed).

**Label example:** terminal phases `… success, success` → `next.done = 1` on the last exported frame; `next.success = 1` on that frame too. Failed episodes still get `next.done = 1` on the last frame; `next.success = 0`.

### Episode definition

- **Start:** `cgn_teleop_trial` accepts a grasp preview and calls `begin_episode` (bag warm-up at home, then approach).
- **End:** EE reaches lift handoff (`LIFT_Z` for teleop, or after auto lift); `end_episode` then place/home are **not** recorded.
- No recording between trials.
- Fully automated vs human: check `intervention` max / zarr attr `intervention_used`.

## Load

```python
from lerobot.datasets.lerobot_dataset import LeRobotDataset

ds = LeRobotDataset("benudavis/cluttered_grasp")
print(ds)
frame = ds[0]
# EE state / action:
#   frame["observation.state"]         # (8,) eef xyz+quat + gripper
#   frame["action"]                   # (7,) delta_xyz + delta_rpy + abs gripper next
#   frame["observation.joint_state"]  # (7,) joints + gripper
#   frame["observation.joint_action"] # (7,) next joints + gripper
#   frame["observation.cgn_grasp_pose"]  # (7,) constant CGN target
# RGB / tactile: frame["observation.images.center_cam"], ...
# Depth: frame["observation.images.center_cam_depth"]  # 480×848×1 mm, unaligned 848×480 capture
# Phases / returns:
#   frame["episode_state"]    # 0 reach / 1 grasp_lift
#   frame["intervention"]     # 1 if teleop used
#   frame["grasp_state"]      # int64 phase id (contact labels)
#   frame["next.success"]     # 1.0 on last exported frame if episode ends in success
#   frame["next.done"]        # 1.0 on last exported frame (every episode)
```

## Collection / conversion notes

- ROS bags → one zarr episode per bag (`bag2dataset` under `~/venvs/clutter`, zarr≥3).
- Episodes are service-gated by `cgn_teleop_trial` (begin after preview Enter with warm-up; end at lift handoff).
- Offline rebuild: `scripts/zarr_to_lerobot.py --fps 30 --depth-mode video12` over `~/EDG_Experiment/clutter/**/*.zarr` (skips `clutter/old/`).
- Phase labels: `scripts/label_grasp_states.py` (Streamlit) writes `data/obs/policy/grasp_state` and, on **Save** / **Save all**, derived `next_success` / `next_done` on each episode zarr.
- Converter sets `next.done` / `next.success` with the same terminal-frame rules as
  the labeler (last frame; success from terminal `grasp_state`).
- Trial stats: `python scripts/plot_trial_outcomes.py --zarr-root … --out …` (or `zarr_to_lerobot.py --trial-stats-out …`).
- Bag convert also skips leading frames with empty tactile / NaN policy before writing zarr.
- Auto-label may set contact/success from tactile blob area; only terminal success runs (touching episode end) stay `success`.
- Actions: EE delta pose + absolute next gripper; joint absolute next (see `scripts/lerobot_convert/actions.py`).
- Upload: `scripts/upload_lerobot_hf.py` (copies this card to the dataset root as `README.md`).