Upload README.md

README.md

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+---
+language:
+  - en
+  - zh
+license: cc-by-sa-4.0
+tags:
+  - robotics
+  - tactile
+  - manipulation
+  - embodiment-agnostic
+  - multimodal
+  - video
+  - teleoperation
+  - lerobot
+  - grasping
+  - dexterous-manipulation
+  - multi-environment
+pretty_name: "Embodiment-Agnostic Tactile Manipulation Dataset"
+size_categories:
+  - 1K<n<10K
+
+---
+
+# 🤖 Embodiment-Agnostic Tactile Manipulation Dataset
+
+A growing, multimodal robotic manipulation dataset featuring **synchronized dual-camera video, dual-hand tactile sensing, and hand pose tracking** across diverse real-world environments. All demonstrations are collected via human teleoperation — without any specific robot embodiment — and annotated at the action-segment level with rich categorical labels.
+
+> [!NOTE]
+> **This is a living dataset.** New environments, tasks, and objects will be added over time. The current release covers **chemistry laboratory** operations. Future releases will expand to additional scenes such as kitchens, workshops, offices, grocery stores, and more. See the [Annotation Schema](#-annotation-schema) for the full list of supported environments and object categories.
+
+## 📋 Dataset Summary
+
+| Property | Value |
+|---|---|
+| **Design philosophy** | Embodiment-agnostic — human hand demonstrations with tactile & visual sensing, transferable to any robot morphology |
+| **Environments** | Multi-scene (currently: chemistry lab; planned: kitchen, workshop, office, store, etc.) |
+| **Current tasks** | Mortar & pestle grinding, Crucible tongs transfer |
+| **Total annotated segments** | **1,001** (and growing) |
+| **Total raw episodes** | ~300+ |
+| **Modalities** | Ego-view video, side-view video, dual-hand tactile pressure (256-d × 2), hand pose (72-d) |
+| **Video resolution** | 640 × 480 @ 30 FPS |
+| **Video codec** | AV1 (raw), H.264/MP4 (annotated segments) |
+| **Tactile sensor** | Dual tactile gloves, 256 channels per hand, float32 |
+| **Total size** | ~8.6 GB (current release) |
+| **Data format** | LeRobot v3.0 (raw) + JSONL annotations + Apache Parquet (tactile) |
+
+
+---
+
+## 💡  Why Embodiment-Agnostic?
+
+Traditional robot manipulation datasets are tightly coupled to a specific robot platform. This dataset takes a fundamentally different approach:
+
+- **Human hands as the universal demonstrator** — Demonstrations are performed by human operators wearing sensorized tactile gloves, capturing the natural dexterity, force modulation, and multi-finger coordination that is difficult to obtain from any single robot embodiment.
+- **Transferable to any morphology** — The rich multi-modal signals (vision + tactile + hand pose) can be retargeted to different robot hands, grippers, or end-effectors via learned or analytic mappings.
+- **Scalable across environments** — The portable data collection rig allows rapid deployment in diverse real-world settings without robot-specific setup, enabling the dataset to grow across many environments and tasks.
+
+---
+
+## 🗂️ Available Sub-Datasets
+
+The dataset is organized by recording session. Each sub-dataset is a self-contained package with raw data and cleaned annotations. Sub-datasets are grouped below by environment and task.
+
+### 🧪 Chemistry Lab
+
+#### Task 1: Mortar and Pestle Grinding
+
+| Sub-Dataset | Segments | Action Sequence | Size |
+|---|---|---|---|
+| `0508_1_mortar_pestle` | 214 | picking up → grinding → placing | 1.5 GB |
+| `0508_2_mortar_pestle` | 201 | picking up → grinding → placing | 2.4 GB |
+| **Subtotal** | **415** | | **3.9 GB** |
+
+#### Task 2: Crucible Tongs Transfer
+
+| Sub-Dataset | Segments | Action Sequence | Size |
+|---|---|---|---|
+| `0508_3_crucible_tongs_transfer` | 349 | picking up → clamping & transferring → placing → restoring | 1.5 GB |
+| `0508_4_crucible_tongs_transfer` | 237 | picking up → clamping & transferring → placing | 3.2 GB |
+| **Subtotal** | **586** | | **4.7 GB** |
+
+### 🔜 Coming Soon
+
+Additional environments and tasks are in preparation, including but not limited to:
+
+| Environment | Example Tasks | Status |
+|---|---|---|
+| Kitchen | Object sorting, tool use | Planned |
+| Workshop | Assembly, tool manipulation | Planned |
+| Office | Stationery handling, organizing | Planned |
+| Grocery Store | Product picking, shelf stocking | Planned |
+| Living Room | Everyday object manipulation | Planned |
+
+> Each new environment will follow the same data format and annotation schema, ensuring full compatibility across the entire dataset.
+
+---
+
+## 🏷️ Annotation Schema
+
+The annotation schema is designed to be **environment-agnostic and extensible**. New environments, objects, and actions can be added without breaking existing data.
+
+Each annotated segment is labeled with the following multi-dimensional categorical attributes:
+
+### Label Categories
+
+| Category | Type | Description |
+|---|---|---|
+| `environment` | single-select | Scene / location of the task |
+| `object` | single-select | Object(s) being manipulated |
+| `action` | single-select | Fine-grained action label |
+| `grasp_type` | single-select | Grasp taxonomy classification |
+| `notes` | free-text | Annotator notes per segment |
+
+### Supported Environments (Expandable)
+
+The schema currently supports the following environments, with new entries added as data collection expands:
+
+```
+hardware store · office 1 · office 2 · grocery store 1 · grocery store 2
+workshop · kitchen · sports store · bedroom · plant store
+restaurant 1 · restaurant 2 · living room · biochemistry lab
+wet lab bench · solution preparation station · distillation station
+fume hood · sterile workbench · analytical instrument station
+cold storage area · waste disposal area · chemistry lab · ...
+```
+
+### Supported Grasp Types
+
+```
+Small Diameter · Tip Pinch · Prismatic 2 Finger · Prismatic 3 Finger
+Index Finger Extension · Medium Wrap · Palmar · Fixed Hook
+Light Tool · Precision Sphere · ...
+```
+
+### Current Action Labels by Task
+
+**Mortar & Pestle Grinding:**
+```
+picking up  →  grinding  →  placing
+```
+
+**Crucible Tongs Transfer:**
+```
+picking up  →  clamping and transferring  →  placing  [→ restoring object position]
+```
+
+### Action Distribution (Current Release)
+
+| Action | 0508_1 | 0508_2 | 0508_3 | 0508_4 | **Total** |
+|---|---|---|---|---|---|
+| picking up | 72 | 67 | 116 | 79 | **334** |
+| grinding | 72 | 67 | — | — | **139** |
+| placing | 70 | 67 | 116 | 79 | **332** |
+| clamping and transferring | — | — | 116 | 79 | **195** |
+| restoring object position | — | — | 1 | — | **1** |
+
+---
+
+## 📁 Directory Structure
+
+Each sub-dataset follows a consistent structure:
+
+```
+<dataset_root>/
+├── README.md                              ← This file (top-level)
+├── <session_id>_<task_name>/              ← Sub-dataset package
+│   ├── README.md                          ← Sub-dataset description
+│   ├── dataset_metadata.json              ← Machine-readable metadata
+│   ├── checksums.sha256                   ← Package-level integrity checksums
+│   ├── raw/
+│   │   └── lerobot/<raw_id>/             ← Original LeRobot v3.0 dataset
+│   │       ├── data/                      ←   Parquet data files (tactile, state, etc.)
+│   │       ├── videos/                    ←   Full-episode AV1 video streams
+│   │       ├── images/                    ←   (if applicable)
+│   │       ├── meta/                      ←   info.json, stats.json, tasks.parquet, ...
+│   │       └── sync_diagnostics/          ←   Timing / synchronization logs
+│   └── annotated/
+│       ├── annotations.jsonl              ← All segment annotations (1 JSON per line)
+│       ├── schema.json                    ← Annotation schema definition
+│       ├── manifest.json                  ← File manifest for all segments
+│       ├── validation_report.json         ← Automated QA report
+│       ├── release_report.json            ← Release summary
+│       ├── checksums.sha256               ← Annotated-subset checksums
+│       └── segments/
+│           └── train/
+│               └── rbt_epXXXXXX_sXXXXXX/ ← Per-segment directory
+│                   ├── ego.mp4            ← Ego-view video clip
+│                   ├── side.mp4           ← Side-view video clip
+│                   ├── data.parquet       ← Tactile + state data
+│                   └── meta.json          ← Segment metadata & labels
+├── ...                                    ← More sub-datasets
+```
+
+---
+
+## 🎯 Modalities in Detail
+
+### 1. Visual — Dual-Camera Video
+
+Each episode is recorded from two synchronized camera viewpoints:
+
+| Camera | Key | Resolution | FPS | Codec |
+|---|---|---|---|---|
+| **Ego-view** | `observation.images.ego` | 640 × 480 | 30 | AV1 (raw) / H.264 (annotated) |
+| **Side-view** | `observation.images.side` | 640 × 480 | 30 | AV1 (raw) / H.264 (annotated) |
+
+- **Raw episodes**: Full uncut videos stored under `raw/lerobot/*/videos/`.
+- **Annotated segments**: Trimmed video clips per action segment stored as `ego.mp4` and `side.mp4`.
+
+### 2. Tactile — Dual-Hand Pressure Arrays
+
+High-resolution tactile data from sensorized gloves, recorded at 30 Hz:
+
+| Channel | Key | Shape | Dtype | Description |
+|---|---|---|---|---|
+| Left hand | `observation.tactile_left` | (256,) | float32 | Raw pressure values from left-hand tactile glove |
+| Right hand | `observation.tactile_right` | (256,) | float32 | Raw pressure values from right-hand tactile glove |
+
+- Tactile routing protocol: Header (4 bytes) + Sequence (1 byte) + Type (1 byte) + Data
+- Type `0x01` → Left hand, Type `0x02` → Right hand
+- Per-segment tactile data is stored in `data.parquet` files
+
+### 3. Hand Pose — Teleoperation State
+
+Full articulated hand pose captured via the UDexReal hand-tracking system:
+
+| Key | Shape | Dtype | Description |
+|---|---|---|---|
+| `observation.udexreal` | (72,) | float32 | Dual-hand bone positions, rotations, scales, and finger joint parameters |
+
+The 72-dimensional vector encodes:
+- Head bone: Location (3D), Parent, Rotation (3D), Scale (3D) — 10 dims
+- Left hand: Calibration status + 24 joint parameters + joystick/button states — 31 dims
+- Right hand: Calibration status + 24 joint parameters + joystick/button states — 31 dims
+
+---
+
+## 🔖 Segment ID Convention
+
+All segment IDs follow the format:
+
+```
+rbt_ep{EPISODE:06d}_s{SEGMENT:06d}
+```
+
+- `ep` = Episode index (from the original LeRobot dataset)
+- `s` = Globally unique segment index within the sub-dataset
+
+Example: `rbt_ep000002_s000001` = Episode 2, Segment 1
+
+---
+
+## 📊 JSONL Annotation Format
+
+Each line in `annotations.jsonl` is a self-contained JSON object:
+
+```json
+{
+  "segment_id": "rbt_ep000002_s000001",
+  "episode_idx": 2,
+  "start_frame": 6,
+  "end_frame": 94,
+  "labels": {
+    "environment": "chemistry lab",
+    "object": "mortar and pestle",
+    "action": "picking up",
+    "grasp_type": "Small Diameter"
+  },
+  "outcome": {
+    "success_frame": null,
+    "final_success": null,
+    "events": []
+  },
+  "notes": "研磨物体",
+  "workflow_status": "approved"
+}
+```
+
+### Per-Segment `meta.json` Format
+
+```json
+{
+  "segment_id": "rbt_ep000002_s000001",
+  "source": {
+    "dataset_id": "0508",
+    "episode_idx": 2,
+    "start_frame": 6,
+    "end_frame": 94,
+    "start_time_sec": 0.2,
+    "end_time_sec": 3.133,
+    "fps": 30.0
+  },
+  "labels": {
+    "environment": "chemistry lab",
+    "object": "mortar and pestle",
+    "action": "picking up",
+    "grasp_type": "Small Diameter"
+  },
+  "outcome": { ... },
+  "notes": "研磨物体"
+}
+```
+
+---
+
+## 🚀 Quick Start
+
+### Loading Annotations
+
+```python
+import json
+
+annotations = []
+with open("0508_1_mortar_pestle/annotated/annotations.jsonl") as f:
+    for line in f:
+        annotations.append(json.loads(line))
+
+# Filter by action
+grinding_segments = [a for a in annotations if a["labels"]["action"] == "grinding"]
+print(f"Grinding segments: {len(grinding_segments)}")
+```
+
+### Loading Tactile Data
+
+```python
+import pandas as pd
+
+# Load per-segment tactile data
+df = pd.read_parquet(
+    "0508_1_mortar_pestle/annotated/segments/train/rbt_ep000002_s000001/data.parquet"
+)
+print(df.columns.tolist())
+print(df.shape)
+```
+
+### Loading Segment Video
+
+```python
+import cv2
+
+cap = cv2.VideoCapture(
+    "0508_1_mortar_pestle/annotated/segments/train/rbt_ep000002_s000001/ego.mp4"
+)
+fps = cap.get(cv2.CAP_PROP_FPS)
+frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+print(f"FPS: {fps}, Frames: {frame_count}")
+cap.release()
+```
+
+### Using with LeRobot (Raw Data)
+
+The `raw/lerobot/` directories are compatible with the [LeRobot](https://github.com/huggingface/lerobot) framework (codebase v3.0):
+
+```python
+# Raw dataset can be loaded with LeRobot's dataset loader
+# Refer to https://github.com/huggingface/lerobot for details
+```
+
+---
+
+## ✅ Data Quality & Validation
+
+- All annotated segments have passed automated validation (0 P0 critical errors)
+- Validation issues are limited to P1 informational notes (`P1_LEGACY_APPROVED_NEEDS_REVIEW` — indicating segments migrated from a legacy annotation workflow)
+- SHA-256 checksums are provided at both the package level (`checksums.sha256`) and the annotated subset level (`annotated/checksums.sha256`)
+
+### Validation Summary (Current Release)
+
+| Sub-Dataset | P0 (Critical) | P1 (Info) | P2 (Warning) |
+|---|---|---|---|
+| 0508_1_mortar_pestle | 0 | 214 | 0 |
+| 0508_2_mortar_pestle | 0 | 201 | 0 |
+| 0508_3_crucible_tongs_transfer | 0 | 345 | 0 |
+| 0508_4_crucible_tongs_transfer | 0 | 237 | 0 |
+
+### Integrity Verification
+
+```bash
+# Verify full package integrity
+cd 0508_1_mortar_pestle
+sha256sum -c checksums.sha256
+
+# Verify annotated subset only
+cd annotated
+sha256sum -c checksums.sha256
+```
+
+---
+
+## 📝 Processing Notes
+
+### Label Normalization
+- In sub-datasets `0508_1` and `0508_4`, the original `moving` and `picking up` stages were merged into a single `picking up` label to ensure consistency across the dataset.
+- In `0508_4`, the original `adjusting` stage was normalized to `clamping and transferring`.
+
+### Scope of 0508_4
+The original `0508_4` LeRobot recording contains more than one task. Episodes 001–096 correspond to the crucible-tongs transfer task, while episodes starting from 097 correspond to stirring a beaker solution with a glass rod. Only the crucible-tongs transfer subset (79 cleaned episodes) is included in the annotated release. Episodes 080 and 095 were excluded during quality control.
+
+---
+
+## 🏗️ Data Collection Setup
+
+| Component | Specification |
+|---|---|
+| **Teleoperation system** | UDexReal hand-tracking gloves with integrated tactile sensing |
+| **Cameras** | Dual RGB cameras (ego-view + side-view), 640×480, 30 FPS |
+| **Tactile sensors** | Dual tactile gloves, 256 pressure channels per hand |
+| **Recording framework** | LeRobot v3.0 |
+| **Annotation tool** | Custom JSONL-based annotation pipeline with schema validation |
+| **Data synchronization** | Hardware-triggered, verified via `sync_diagnostics/` |
+
+The entire collection rig is portable and can be deployed across different environments without any robot-specific hardware, enabling rapid scaling to new scenes and tasks.
+
+---
+
+
+---
+
+## 📖 Citation
+
+If you use this dataset in your research, please cite:
+
+```bibtex
+@misc{tactile_manipulation_2026,
+  title     = {Embodiment-Agnostic Tactile Manipulation Dataset},
+  author    = {Rimbot},
+  year      = {2026},
+  publisher = {Hugging Face},
+  note      = {A growing multimodal dataset with synchronized dual-camera
+               video, dual-hand tactile sensing, and hand pose tracking
+               for dexterous manipulation across diverse real-world environments}
+}
+```
+
+---
+
+## 📬 Contact
+
+For questions, issues, or collaboration inquiries, please open an issue on this Hugging Face dataset repository.
+
+---
+
+## 📅 Changelog
+
+| Date | Update |
+|---|---|
+| 2026-05-23 | Initial release — Chemistry Lab: mortar & pestle grinding (×2) + crucible tongs transfer (×2) |