| --- |
| license: cc-by-4.0 |
| task_categories: |
| - robotics |
| tags: |
| - LeRobot |
| - dexterous-manipulation |
| - point-cloud |
| - xarm7 |
| - leap-hand |
| configs: |
| - config_name: default |
| data_files: data/*/*.parquet |
| --- |
| |
| <div align="center"> |
|
|
| # DexMulti: Grasp + Pull |
|
|
| [](https://dexmulti.github.io/) |
| [](https://arxiv.org/abs/2603.11655) |
| [](https://github.com/Msornerrrr/dexmulti) |
|
|
| <video src="https://huggingface.co/datasets/HJ666/dexmulti_grasp_pull/resolve/main/media/demo.mp4" controls autoplay loop muted playsinline width="100%"></video> |
|
|
| <sub>One teleoperated demonstration: the two RGB cameras (left); the robot, the segmented object clouds with hand contact, and the end-effector path coloured by skill (right).</sub> |
|
|
| </div> |
|
|
| Teleoperated demonstrations of the **Grasp + Pull** task (paper: main experiments): 38 demonstrations, the complete training set used for the paper's experiments. |
|
|
| Paper: *Concurrent Prehensile and Nonprehensile Manipulation: A Practical Approach to Multi-Stage Dexterous Tasks* |
| (IROS 2026, [arXiv:2603.11655](https://arxiv.org/abs/2603.11655)). Code: <https://github.com/Msornerrrr/dexmulti>. Full documentation (conventions, loading without LeRobot, npz conversion): <https://github.com/Msornerrrr/dexmulti/blob/main/docs/dataset.md>. |
|
|
| **Task:** Grasp an object from the table, pull open a drawer by its handle, and place the object in the drawer. |
|
|
| | | | |
| |---|---| |
| | robot | xArm7 arm + LEAP Hand (right), teleoperated with DexCap | |
| | cameras | 2x Intel RealSense L515 (RGB 640x480) | |
| | episodes / frames | 38 / 8840 (length 187–330, mean 232.6) | |
| | rate | 10 Hz | |
| | format | LeRobot v3.0, videos H.264 (yuv420p) | |
|
|
| ## Features |
|
|
| | feature | shape | description | |
| |---|---|---| |
| | `observation.images.cam1`, `observation.images.cam2` | 480x640x3 video | RGB of the two cameras | |
| | `observation.state` | (29,) float32 | see below | |
| | `action` | (22,) float32 | see below | |
| | `observation.pointcloud.object` | (512, 3) float32 | segmented point cloud of the first (grasped) object, robot base frame [m] | |
| | `observation.pointcloud.drawer` | (512, 3) float32 | segmented point cloud of the drawer (key name kept from the code base) | |
| | `observation.pointcloud.hand` | (512, 3) float32 | points on the LEAP Hand surface from forward kinematics | |
| | `observation.contact.object`, `observation.contact.drawer` | (512, 1) float32 | per-point hand contact score in [0, 1] of the matching cloud | |
| | `observation.skill` | int64 | 0: not in a skill (approach / transition), 1: skill 1 (first object), 2: skill 2 (the drawer) | |
| | `task` | string | language instruction (one per dataset) | |
|
|
| `observation.state`: |
|
|
| | index | source key | meaning | |
| |---|---|---| |
| | 0–5 | `eef_pose` | measured end-effector pose: x, y, z [m], roll, pitch, yaw [rad] (scipy Euler `xyz`) | |
| | 6–12 | `arm_state` | xArm7 joint positions [rad] | |
| | 13–28 | `hand_state` | LEAP Hand joint positions [rad] (LEAP ROS order: 4 per finger, thumb last) | |
|
|
| `action` (what the robot was commanded at this step, 10 Hz): |
|
|
| | index | source key | meaning | |
| |---|---|---| |
| | 0–5 | `arm_cmd` | commanded end-effector pose: x, y, z [m], roll, pitch, yaw [rad] | |
| | 6–21 | `hand_cmd` | LEAP Hand joint commands [rad] | |
|
|
| Element names are in `meta/info.json`. |
|
|
| ## Frames and conventions |
|
|
| - All poses and point clouds are in the xArm7 base frame (`link_base`), metres. Orientations are scipy Euler |
| `"xyz"` angles in radians; roll is near ±π, so its plot wraps. |
| - Point clouds come from the two depth cameras (fused, segmented, 512 points per object) and are the inputs used by |
| DexMulti. Depth images and masks are not included. |
| - `observation.skill` is derived from the skill keyframes (`task1_start..task1_end` = 1, |
| `task2_start..task2_end` = 2, inclusive). |
| - `timestamp` is `frame_index / 10`; the original wall-clock times are in `dexmulti/episodes.json`. |
|
|
| ## DexMulti extras (`dexmulti/`) |
|
|
| Not part of the LeRobot schema; used by the DexMulti code base: |
|
|
| - `episodes.json`: per `episode_index` the original recording name, length, source set and wall-clock times. |
| - `keyframes/<episode>.json`: skill keyframes as used to build the library. |
| - `library/dual_task_policy_chamfer.npz`: the skill library built from these demonstrations, exactly as run on the robot (pickle-free format, load with `dexmulti.library.load_library`). |
| - `keyframe_overlaps.json`: recordings whose two keyframe ranges overlap, with the resulting `observation.skill` runs. |
| - `cameras.json`: intrinsics (fx, fy, cx, cy) and extrinsics `T_base_cam` (camera optical frame to robot base) of |
| both cameras; constant for the whole dataset. |
|
|
| Load as DexMulti episodes (no `lerobot` or `torch` needed): |
|
|
| ```python |
| from dexmulti.data.lerobot import LeRobotEpisodes |
| ds = LeRobotEpisodes("<path or repo id>") |
| ep = ds.episode(0) # dict: keys of dexmulti/data/episode.py + skill |
| kf = ds.keyframes(0) # task1_start, task1_end, task2_start, task2_end |
| ``` |
|
|
| or with LeRobot: `LeRobotDataset("HJ666/dexmulti_grasp_pull")`. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{jiang2026concurrent, |
| title = {Concurrent Prehensile and Nonprehensile Manipulation: A Practical Approach to Multi-Stage Dexterous Tasks}, |
| author = {Jiang, Hao and Wu, Yue and Wang, Yue and Sukhatme, Gaurav S. and Seita, Daniel}, |
| booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, |
| year = {2026} |
| } |
| ``` |
|
|
| ## License |
|
|
| [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/). Please cite the paper when using the data. |
|
|
