--- license: cc-by-4.0 task_categories: - robotics tags: - robotics - tactile - manipulation - multimodal - gelsight - realsense - motion-capture pretty_name: React (Tactile-Visual Manipulation) size_categories: - 10K **30 episodes · 138.4 min total · 87.9 min (66%) of confirmed bimanual tactile contact · 3× RGB-D cameras + 2× GelSight + 3-body OptiTrack.** ## At a glance | | | |---|---| | Tasks | `motherboard` (more coming) | | Episodes | 30 | | Total duration | **138.4 min** (median 4 min/episode, longest 19 min) | | Tactile contact | **87.9 min / 66% of frames** (4,136 contact events, median 0.73 s each) | | Cameras | 3× Intel RealSense D415 (color + depth, 480×640, 30 FPS) | | Tactile | 2× GelSight Mini (left / right, 480×640, ~25 FPS) | | Motion capture | OptiTrack VRPN, 3 rigid bodies, ~120 Hz | | License | CC-BY-4.0 | ![Comparison table](figures/dataset_figures/F7_comparison_table.png) ## Recording setup | Stream | Hardware | Native shape | Rate | |---|---|---|---| | 3× RealSense color | Intel D415 (serials `143322063538`, `104122062574`, `217222066989`) | 480×640×3 uint8 (BGR) | 30 FPS | | 3× RealSense depth | same | 480×640 uint16 (mm) | 30 FPS | | 2× GelSight tactile | GelSight Mini (left / right) | 480×640×3 uint8 | ~25 FPS, resampled to camera ticks | | 3× OptiTrack rigid bodies | `motherboard`, `sensor_left`, `sensor_right` | 7-vector (x, y, z, qx, qy, qz, qw) | ~120 Hz | All streams share a common monotonic timestamp axis recorded under `timestamps`. Per-tracker OptiTrack streams carry their own higher-rate timestamps under `optitrack//timestamps`. ## Tasks The dataset is organized **task-first** so new tasks can be added without renaming or recompute. | Task | Description | Dates | Episodes | |---|---|---|---| | `motherboard` | Bimanual manipulation of components on a computer motherboard | 2026-03-23, 2026-05-10, 2026-05-11 | 30 | `tasks.json` at the repo root is the source of truth for the task registry. ## Episode previews Each `figures/episode_previews/motherboard//episode_NNN.gif` shows the first 2 minutes of that episode at 15× speed (≈8 s loop, 3-panel layout: overhead camera | tactile left | tactile right). Browse them in the [`figures/episode_previews`](figures/episode_previews) folder of this repo. ## Statistics & analysis ### Episode length ![Episode length](figures/dataset_figures/F1_episode_length_histogram.png) Most episodes run 1–10 min; the median is **4 min** — roughly 8× longer than BridgeData V2's typical 30 s demo. The longest episode is 19 min. ### Contact event durations ![Contact event durations](figures/dataset_figures/F2_contact_event_duration_histogram.png) 4,136 contact events total. The typical contact event lasts ≈ **0.7 s** (median), with a long tail out to 33 s — useful for grasp/contact-classification downstream tasks. ### Where on the gel does contact land? ![Contact heatmap](figures/dataset_figures/F3_contact_heatmap.png) Both sensors show contact concentrated in the central ~50% of the gel surface, dropping off toward the edges. The left gel has discrete bright spots from repeated contacts with specific features. ### Tactile signal is real and varied (not flat noise) ![Tactile montage](figures/dataset_figures/F4_tactile_pattern_montage.png) 16 random contact frames sampled across the dataset — discrete pins, edges, smooth surfaces, multi-object contact. ### Bimanual workspace ![Pose trajectory](figures/dataset_figures/F5_pose_trajectory_3d.png) Multi-view projection of the longest episode (2026-05-11 / ep_017, 19 min). Left (blue) and right (orange) sensors operate over a ~30 × 40 × 30 cm workspace. ### Tactile is independent of motion ![Cross-modal correlation](figures/dataset_figures/F6_cross_modal_correlation.png) Sensor velocity vs tactile intensity is **essentially uncorrelated** (r ≈ +0.04 / −0.05). Tactile carries information that is **not** explained by pose+velocity — a direct argument for the value of including tactile in policy / world-model training. ### Per-episode summary ![Per-episode summary](figures/dataset_figures/F8_per_episode_summary.png) Detailed table also exported as CSV: [`figures/dataset_figures/F8_per_episode_summary.csv`](figures/dataset_figures/F8_per_episode_summary.csv). ## Repository layout ``` tasks.json # registry processed/ └─ mode1_v1/ └─ / └─ / ├─ episode_000.pt ├─ episode_000.contact.json └─ ... figures/ ├─ contact_intensity_full.png # tactile intensity over full dataset (waveform view) ├─ contact_intensity_20min.png # 20-min zoom of the same ├─ episode_previews///episode_*.gif # per-episode GIF previews └─ dataset_figures/ # F1–F8 statistics and analysis figures ``` The `processed/mode1_v1/` view is a **task-specific slice** of the underlying raw recordings, not the full sensor suite. It was produced by `twm/preprocess.py` + `twm/contact_index.py` from a private raw HDF5 mirror. ## `processed/mode1_v1/` schema Each `episode_*.pt` is a Python dict loadable with `torch.load(..., weights_only=False)`. | Key | Shape | dtype | Description | |---|---|---|---| | `view` | `(T, 3, 128, 128)` | uint8 | Overhead camera (`realsense/cam0/color`), center-cropped to square then bilinear-resized to 128×128 | | `tactile_left` | `(T, 3, 128, 128)` | uint8 | Left GelSight, same crop/resize | | `tactile_right` | `(T, 3, 128, 128)` | uint8 | Right GelSight, same crop/resize | | `timestamps` | `(T,)` | float64 | Camera timestamps (seconds, monotonic clock) | | `sensor_left_pose` | `(T, 7)` | float32 | Left GelSight rigid body OptiTrack pose, nearest-neighbor aligned to camera timestamps | | `sensor_right_pose` | `(T, 7)` | float32 | Right GelSight rigid body OptiTrack pose, same alignment | | `tactile_{left,right}_intensity` | `(T,)` | float32 | Per-frame mean per-pixel L2 distance from a contact-free reference frame | | `tactile_{left,right}_area` | `(T,)` | float32 | Per-frame fraction of pixels with L2 diff > `tau` | | `tactile_{left,right}_mixed` | `(T,)` | float32 | Mean of (diff × mask), captures intensity restricted to contact pixels | | `_contact_meta` | dict | — | Per-episode contact metadata: `tau`, drift between first/p01 reference frames, p01 reference indices, the chosen reference RGB frames, etc. | Each `.contact.json` is a small summary of the metric distributions plus drift diagnostics, intended for filtering / sanity checking without loading the full tensors. ### Contact metric definition For each tactile sensor independently: 1. Pick a contact-free **reference frame**: the ~0.1th-percentile-quietest frame by mean L2 distance to the temporal median (`reference_strategy = "p01"`). 2. For each frame `t`, compute per-pixel `diff[t, x, y] = || frame[t, :, x, y] − ref[:, x, y] ||_2` (RGB L2 over channels). 3. Then: - `intensity[t] = mean(diff[t])` - `area[t] = mean(diff[t] > tau)` (default `tau = 8.0` on the uint8 scale) - `mixed[t] = mean(diff[t] * (diff[t] > tau))` `_contact_meta["drift_warning"]` is `True` if either sensor's drift (L2 distance between the first frame and the p01-reference frame) exceeds `2·tau`; in this release no episode triggers it. ## Quick start Load one task via `datasets`: ```python from datasets import load_dataset ds = load_dataset("yxma/React", "motherboard", split="train") # Each row is one .pt file path; the actual tensors live inside. ``` Or load a single episode directly: ```python import torch from huggingface_hub import hf_hub_download path = hf_hub_download( repo_id="yxma/React", repo_type="dataset", filename="processed/mode1_v1/motherboard/2026-05-11/episode_003.pt", ) ep = torch.load(path, weights_only=False) print(ep["view"].shape, ep["tactile_left_intensity"].shape) # torch.Size([10032, 3, 128, 128]) torch.Size([10032]) ``` Load contact metadata only (much smaller — useful for filtering): ```python import json path = hf_hub_download( repo_id="yxma/React", repo_type="dataset", filename="processed/mode1_v1/motherboard/2026-05-11/episode_003.contact.json", ) meta = json.load(open(path)) print(meta["drift_left"], meta["drift_right"], meta["drift_warning"]) ``` ## Known caveats - **Missing / dropped episodes** on `motherboard/2026-05-11`: - `episode_000` and `episode_002` — short test recordings (8.8 s and 10.4 s) with no tactile contact on either sensor; intentionally excluded. - `episode_001` — lost at recording time (HDF5 superblock never finalized when the writer was killed mid-write); intentionally absent. - The remaining episode IDs are non-contiguous as a result. Don't infer ordering from filename gaps. - **Lossy resize**: the 128×128 `view` and tactile fields are downsampled from native 480×640. Native resolution is **not** preserved in this release. - **Single camera**: only `realsense/cam0/color` is included. The other two RealSense views and all depth streams are not in `processed/mode1_v1/`. - **OptiTrack alignment**: the per-step poses are nearest-neighbor matched to camera ticks. The full ~120 Hz pose streams are not preserved here. - **Mode is opinionated**: contact metrics depend on the chosen `tau` and the p01 reference strategy. If you want a different `tau`, re-deriving from raw is necessary. ## Roadmap - **More tasks** — registry in `tasks.json` will grow. - **LeRobot-format full-fidelity** variant (`lerobot/v1.0/`) is planned. It will include all three RealSense color and depth streams, GelSight at native resolution (FFV1 lossless), full-rate OptiTrack pose tracks for all three rigid bodies, and HF-native browser previews. The current `processed/mode1_v1/` slice will remain as a stable training-task view. ## Citation If you use this dataset, please cite (TODO: add bibtex).