--- license: cc-by-4.0 task_categories: - robotics tags: - lerobot - tactile - manipulation - project-aria - egocentric size_categories: - n<1K --- # FEEL-Benchmark A multimodal egocentric manipulation dataset combining **Project Aria** smart-glasses recordings (RGB video, eye gaze, hand tracking, IMU) with synchronized **Paxini** tactile-glove force readings. Released in [LeRobot v3.0](https://github.com/huggingface/lerobot) format (GR00T path variant). ## Overview - **26 trials**, **700 episodes**, **~65.8 min** of segmented manipulation, ~2.0 GB - **Recording dates**: 2026-01-10, 2026-01-21, 2026-01-28, 2026-04-30, 2026-05-06 - **Camera**: Project Aria RGB (1408×1408, **10 fps**, H.264) - **Tactile**: bilateral force totals (`action.tactile.left.force_total`, `action.tactile.right.force_total`) - **Hand pose**: Aria MPS hand tracking (left + right, validity flags, confidence) - **Gaze**: Aria MPS general eye gaze (yaw/pitch + depth) - **Mean episode length**: 5.6 s (39,497 frames @ 10 fps) ## Dataset statistics ### By recording date | Date | Trials | Episodes | Frames | Duration (min) | |------------|-------:|---------:|-------:|---------------:| | 2026-01-10 | 3 | 42 | 3,565 | 5.9 | | 2026-01-21 | 7 | 137 | 11,106 | 18.5 | | 2026-01-28 | 5 | 132 | 8,481 | 14.1 | | 2026-04-30 | 2 | 82 | 4,761 | 7.9 | | 2026-05-06 | 9 | 307 | 11,584 | 19.3 | | **Total** | **26** | **700** | **39,497** | **65.8** | ### By object category | Category | Trials | Episodes | Frames | Duration (min) | |----------|-------:|---------:|-------:|---------------:| | Bottle | 5 | 237 | 10,811 | 18.0 | | Jelly | 6 | 115 | 10,232 | 17.1 | | Sponge | 3 | 107 | 6,548 | 10.9 | | Water | 4 | 70 | 4,860 | 8.1 | | Wangzai | 4 | 116 | 4,294 | 7.2 | | Coke | 2 | 19 | 1,512 | 2.5 | | Chip | 2 | 36 | 1,240 | 2.1 | The **Bottle** category includes a fill-level gradient (`Empty_bottle_1`, `P25_bottle`, `P50_bottle`, `P75_bottle`, `Full_bottle_1`) for studying tactile cues of liquid mass and slosh. ## Layout Datasets are grouped by recording session date. Trial names encode the manipulation outcome where relevant (e.g. `Chip_intact` = potato chip not crushed, `Chip_crushed` = chip crushed during grasp). ``` FeelAuthors/FEEL-Benchmark/ ├── 20260110/ Jelly_1, Jelly_2, Jelly_3 (3 trials) ├── 20260121/ Half_coke_2, Half_water_1, Jelly_{5,6,7}, Quarter_coke_0, Quarter_water_2 (7 trials) ├── 20260128/ Half_water_{3,4}, Sponge_{1,2,3} (5 trials) ├── 20260430/ Empty_bottle_1, Full_bottle_1 (2 trials) └── 20260506/ Chip_intact, Chip_crushed, Empty_Want_Milk, Empty_wz, P25_bottle, P50_bottle, P75_bottle, Want_Milk, Wz (9 trials) ``` Each `*_lerobot/` directory follows LeRobot v3.0: ``` _lerobot/ ├── meta/ │ ├── info.json # feature schema, fps, episode counts │ ├── episodes.jsonl # per-episode metadata │ ├── stats.json │ └── tasks.jsonl ├── data/chunk-000/episode_NNNNNN.parquet └── videos/chunk-000/observation.images.main/episode_NNNNNN.mp4 ``` ## Feature schema Each row in `episode_*.parquet`: | Field | dtype | shape | Notes | |------------------------------------|-------------|-------|----------------------------------| | `index` | int64 | (1,) | Global frame index | | `episode_index` | int64 | (1,) | | | `frame_index` | int64 | (1,) | Per-episode frame index | | `timestamp` / `timestamp_ns` | float64/int | | Aria device clock | | `observation.state` | float32 | (7,) | Right-hand pose state | | `action` | float32 | (2,) | Action vector | | `status.hands.valid_right` | bool | (1,) | Hand-tracking validity | | `action.tactile.left.force_total` | float32 | (1,) | Total force, left glove (N) | | `action.tactile.right.force_total` | float32 | (1,) | Total force, right glove (N) | | `observation.images.main` | video | 1408×1408×3 | Aria RGB stream | ## Path format note Each `meta/info.json` declares `"path_format": "groot"`. The `data_path` and `video_path` templates match standard LeRobot v3.0 (`data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet`), so the dataset is consumable by both stock LeRobot tooling and NVIDIA Isaac GR00T loaders. ## Sensors - **Project Aria** (RGB, eye-tracking cameras, SLAM cameras, IMUs) with MPS post-processing for gaze + hand tracking - **Paxini tactile glove** for force feedback (totals exported per side; raw per-taxel data not included in this release) ## Loading ```python from datasets import load_dataset ds = load_dataset("FeelAuthors/FEEL-Benchmark", data_files="20260506/P25_bottle_lerobot/data/chunk-000/*.parquet") ``` Or with LeRobot tooling, point a `LeRobotDataset` at a single trial directory. ## License [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). ## Citation ```bibtex @misc{feel_benchmark_2026, title = {FEEL-Benchmark: Egocentric Tactile-Visual Manipulation Dataset}, author = {FeelAuthors}, year = {2026}, url = {https://huggingface.co/datasets/FeelAuthors/FEEL-Benchmark} } ```