| --- |
| license: apache-2.0 |
| task_categories: |
| - robotics |
| tags: |
| - LeRobot |
| - robotics |
| - franka |
| - teleoperation |
| - real-robot |
| pretty_name: object_classification |
| --- |
| |
| # object_classification |
| |
| Real-robot teleoperation demonstrations of the `object_classification` task on a single-arm Franka Research 3 cell, |
| released in four LeRobot layouts. Every layout is a conversion of the same 80 raw episodes |
| (28,569 frames at 10 Hz); the layouts differ only in the LeRobot codebase version and in the |
| action representation. |
|
|
| | directory | LeRobot version | action (`action`) | consumer | |
| |---|---|---|---| |
| | `lerobot_v21_abs_joint/` | v2.1 | 8-D absolute joint targets + gripper | RLDX-1 loader (`episodes.jsonl`, `meta/modality.json`) | |
| | `lerobot_v21_delta_eef/` | v2.1 | 7-D end-effector velocity command + gripper | RLDX-1 loader | |
| | `lerobot_v30_abs_joint/` | v3.0 | 8-D absolute joint targets + gripper | `lerobot` ≥ 0.5 (`LeRobotDataset`), e.g. π0.5 | |
| | `lerobot_v30_delta_eef/` | v3.0 | 7-D end-effector velocity command + gripper | `lerobot` ≥ 0.5 | |
|
|
| The v3.0 layouts were derived from the v2.1 layouts with the official `lerobot` converter |
| (`convert_dataset_v21_to_v30.py`), so the four directories carry identical frames, states and videos. |
|
|
| ## Task |
|
|
| > Place each object from the tray into the drawer, board, or container that contains its matching object. |
|
|
| Every frame carries the task instruction in the `task` field (one task per dataset) and a `subtask` string |
| column that holds the same instruction (reserved for subtask-level labels). |
|
|
| ## Raw data and conversion |
|
|
| Source: DROID-style teleoperation captures (one `teleoperation.h5` per episode, HDF5) recorded with a |
| Meta Quest controller driving the arm through a cartesian-velocity controller at a nominal 10 Hz. |
| Each capture stores, per control step, the measured robot state (`joint_positions`, `gripper_position`, |
| `cartesian_position`, joint velocities and torques), the commanded actions in several spaces |
| (`joint_position`, `cartesian_velocity`, `cartesian_position`, `gripper_position`, …), controller |
| flags, per-camera timestamps and intrinsics, and the camera streams as embedded mp4 bytes |
| (two ZED stereo cameras, left and right eye each, 1280×720). |
|
|
| Conversion rules applied identically to all four layouts: |
|
|
| | field | source in the capture | value | |
| |---|---|---| |
| | `observation.state` (8) | `/observation/robot_state/joint_positions` (7), `gripper_position` (1) | measured joint angles (rad) + measured gripper closedness (0 = open) | |
| | `action` (abs_joint, 8) | `/action/joint_position` (7), `/action/gripper_position` (1) | commanded absolute joint targets (rad) + commanded gripper closedness in [0, 1] | |
| | `action` (delta_eef, 7) | `/action/cartesian_velocity` (6), `/action/gripper_position` (1) | commanded cartesian velocity (vx vy vz wx wy wz, controller units in [-1, 1]) + commanded gripper closedness | |
| | `observation.image.exterior_camera` | exterior ZED 2i, left eye | 448×252 RGB video (AV1, `libsvtav1` crf 30), 10 fps | |
| | `observation.image.wrist_camera` | wrist ZED Mini, left eye | 448×252 RGB video (AV1), 10 fps | |
| | `timestamp`, `frame_index`, `episode_index`, `index`, `task_index` | control-step index | standard LeRobot bookkeeping | |
|
|
| Only the left eye of each stereo pair is kept; frames are resized from 1280×720 to 448×252 (same aspect |
| ratio, no crop). The gripper is a Robotiq 2F; the `state` vector is the same in both action layouts, only |
| the action head differs. The v2.1 layouts include `meta/modality.json` (state `arm` 0:7, `gripper` 7:8; |
| action `arm` 0:7 / `gripper` 7:8 for abs_joint, `eef_velocity` 0:6 / `gripper` 6:7 for delta_eef) and |
| `meta/stats.json` with the quantile statistics used for normalisation. |
| |
| ## Statistics |
| |
| | | value | |
| |---|---| |
| | episodes | 80 | |
| | frames | 28,569 | |
| | fps | 10 | |
| | episode length | 311–418 steps (mean 357) | |
| | cameras | 2 (exterior, wrist), 448×252 | |
| | robot type | `franka_panda` (Franka Research 3 arm, Robotiq 2F gripper) | |
|
|
| ## Loading |
|
|
| ```python |
| # v3.0 layouts (lerobot >= 0.5) |
| from lerobot.datasets.lerobot_dataset import LeRobotDataset |
| ds = LeRobotDataset("Myungkyu/object_classification", root="<local copy>/lerobot_v30_abs_joint") |
| ``` |
|
|
| ```bash |
| # any layout, plain download |
| huggingface-cli download Myungkyu/object_classification --repo-type dataset --include "lerobot_v21_abs_joint/*" --local-dir . |
| ``` |
|
|
| Companion checkpoints trained on these layouts: `Myungkyu/hiwrld-baseline-ckpts-real-robot`. |
|
|
