---
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

[![Website](https://img.shields.io/badge/Project-Website-1f6feb?style=for-the-badge&logo=githubpages&logoColor=white)](https://dexmulti.github.io/)
[![Paper](https://img.shields.io/badge/arXiv-2603.11655-b31b1b?style=for-the-badge&logo=arxiv&logoColor=white)](https://arxiv.org/abs/2603.11655)
[![Code](https://img.shields.io/badge/Code-GitHub-181717?style=for-the-badge&logo=github&logoColor=white)](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.