---
license: apache-2.0
task_categories:
  - robotics
tags:
  - maniparena
  - bimanual
  - manipulation
  - lerobot
  - cvpr2026
pretty_name: ManipArena Dataset
gated: auto
extra_gated_heading: "Access ManipArena Dataset"
extra_gated_description: "Please provide the following information to access the ManipArena dataset. Your request will be approved automatically."
extra_gated_button_content: "Submit and get access"
extra_gated_fields:
  Full Name: text
  Organization / Affiliation: text
  Country: country
  Email: text
  I plan to use this dataset for:
    type: select
    options:
      - Competition participation
      - Academic research
      - Education
      - label: Other
        value: other
  I agree to use this dataset only for research and competition purposes: checkbox
---

# ManipArena Dataset

Training dataset for [**ManipArena**](https://maniparena.x2robot.com), a real-robot benchmark and competition for bimanual manipulation at the [CVPR 2026 Embodied AI Workshop](https://embodied-ai.org/cvpr2026/).

This dataset provides rich multi-modal demonstrations in [LeRobot](https://github.com/huggingface/lerobot) format, covering **20 real-robot tasks** and **3 simulation tasks**. Beyond standard end-effector trajectories, we provide **joint positions, velocities, currents, camera views, and mobile-base states** — giving participants the freedom to explore diverse input representations.

## Dataset Structure

```
maniparena-dataset/
├── real/
│   ├── execution_reasoning/        (10 tasks, ~5,000 episodes)
│   ├── semantic_reasoning/         (5 tasks, ~2,800 episodes)
│   └── mobile_manipulation/        (5 tasks, ~2,900 episodes)
└── sim/
    ├── press_button_in_order/      (60 episodes)
    ├── put_blocks_to_color/        (50 episodes)
    └── pick_fruits_into_basket/    (50 episodes)
```

Each task folder follows LeRobot format:

```
<task>/
    meta/info.json
    meta/tasks.jsonl
    data/chunk-000/episode_000000.parquet
    videos/chunk-000/
        observation.images.faceImg/episode_000000.mp4
        observation.images.leftImg/episode_000000.mp4
        observation.images.rightImg/episode_000000.mp4
```

---

## Real Robot Data

Tabletop tasks (Execution Reasoning + Semantic Reasoning) have **56-dimensional** state/action vectors.
Mobile Manipulation tasks have **62-dimensional** state/action vectors (56D + 6D mobile extras).

### Dimension Layout

**End-effector (index 0–13, 14D):**

| Index | Key | Dim | Description |
|-------|-----|-----|-------------|
| 0–2 | `follow_left_ee_cartesian_pos` | 3 | Left arm position (x, y, z) |
| 3–5 | `follow_left_ee_rotation` | 3 | Left arm rotation (roll, pitch, yaw) |
| 6 | `follow_left_gripper` | 1 | Left gripper open/close |
| 7–9 | `follow_right_ee_cartesian_pos` | 3 | Right arm position (x, y, z) |
| 10–12 | `follow_right_ee_rotation` | 3 | Right arm rotation (roll, pitch, yaw) |
| 13 | `follow_right_gripper` | 1 | Right gripper open/close |

> Coordinate system: **+x** forward, **+y** left, **+z** up.

**Joint — left arm (index 14–34, 21D):**

| Index | Key | Dim | Description |
|-------|-----|-----|-------------|
| 14–20 | `follow_left_arm_joint_pos` | 7 | Left arm joint positions (6 joints + gripper) |
| 21–27 | `follow_left_arm_joint_dev` | 7 | Left arm joint velocities (6 joints + gripper) |
| 28–34 | `follow_left_arm_joint_cur` | 7 | Left arm joint currents (6 joints + gripper) |

**Joint — right arm (index 35–55, 21D):**

| Index | Key | Dim | Description |
|-------|-----|-----|-------------|
| 35–41 | `follow_right_arm_joint_pos` | 7 | Right arm joint positions (6 joints + gripper) |
| 42–48 | `follow_right_arm_joint_dev` | 7 | Right arm joint velocities (6 joints + gripper) |
| 49–55 | `follow_right_arm_joint_cur` | 7 | Right arm joint currents (6 joints + gripper) |

> The last element (index 20, 27, 34, 41, 48, 55) in each 7D joint group is the gripper value.

**Mobile manipulation extras (index 56–61, mobile tasks only, 6D):**

| Index | Key | Dim | Description |
|-------|-----|-----|-------------|
| 56–57 | `head_actions` | 2 | Head rotation (yaw, pitch) |
| 58 | `height` | 1 | Lift mechanism height |
| 59–61 | `velocity_decomposed_odom` | 3 | Chassis velocity (vx, vy, angular velocity) |

> **Tabletop tasks** = 56D (index 0–55).
> **Mobile Manipulation tasks** = 62D (index 0–61).

### Task List — Real Robot

**Execution Reasoning (10 tasks):**

| Task | Episodes | Key Challenge |
|------|----------|---------------|
| `arrange_cup_inverted_triangle` | 528 | Multi-object spatial planning |
| `put_spoon_to_bowl` | 525 | Precision grasping, varied shapes |
| `put_glasses_on_woodshelf` | 513 | Fragile object handling |
| `put_ring_onto_rod` | 517 | Sub-cm insertion precision |
| `put_items_into_drawer` | 510 | Multi-object coordination |
| `pick_items_into_basket` | 532 | Adaptive grasping |
| `pour_water_from_bottle` | 526 | Force control, liquid dynamics |
| `insert_wireline` | 530 | Contact-rich, mm-level accuracy |
| `put_stationery_in_case` | 390 | Multi-object organization |
| `put_blocks_to_color` | 451 | Color-zone matching |

**Semantic Reasoning (5 tasks):**

| Task | Episodes | Key Challenge |
|------|----------|---------------|
| `sort_headphone` | 515 | Recognize headphone type |
| `classify_items_as_shape` | 545 | Map objects to shape categories |
| `press_button_in_order` | 538 | Color-button mapping + sequence |
| `pair_up_items` | 540 | Match pairs by pattern |
| `pick_fruits_into_basket` | 645 | Fruit vs. non-fruit distinction |

**Mobile Manipulation (5 tasks):**

| Task | Episodes | Key Challenge |
|------|----------|---------------|
| `put_clothes_in_hamper` | 540 | Navigate + pick clothes |
| `hang_up_picture` | 576 | Navigate to wall + hang |
| `organize_shoes` | 595 | Navigate + arrange on rack |
| `put_bottle_on_woodshelf` | 630 | Navigate to shelf + place |
| `take_and_set_tableware` | 531 | Navigate + set table |

---

## Simulation Data (28D)

Simulation demonstrations contain **28-dimensional** `observation.state` and `action` vectors, combining end-effector (14D) and joint (14D) data from the same trajectories.

### Dimension Layout

**End-effector (index 0–13):**

| Index | Key | Dim | Description |
|-------|-----|-----|-------------|
| 0–2 | `ee_left_xyz` | 3 | Left arm EE position (x, y, z) |
| 3–5 | `ee_left_rpy` | 3 | Left arm EE rotation (roll, pitch, yaw) |
| 6 | `ee_left_gripper` | 1 | Left gripper |
| 7–9 | `ee_right_xyz` | 3 | Right arm EE position (x, y, z) |
| 10–12 | `ee_right_rpy` | 3 | Right arm EE rotation (roll, pitch, yaw) |
| 13 | `ee_right_gripper` | 1 | Right gripper |

**Joint (index 14–27):**

| Index | Key | Dim | Description |
|-------|-----|-----|-------------|
| 14–19 | `joint_left_pos` | 6 | Left arm joint positions |
| 20 | `joint_left_gripper` | 1 | Left joint gripper |
| 21–26 | `joint_right_pos` | 6 | Right arm joint positions |
| 27 | `joint_right_gripper` | 1 | Right joint gripper |

> The first 14 dimensions (EE) are directly compatible with real-robot index 0–13.

### Task List — Simulation

| Task | Episodes | Real-robot Counterpart |
|------|----------|----------------------|
| `press_button_in_order` | 60 | press_button_in_order |
| `put_blocks_to_color` | 50 | put_blocks_to_color |
| `pick_fruits_into_basket` | 50 | pick_fruits_into_basket |

---

## Camera Views

All tasks include **3 synchronized camera streams** at 480×640 resolution:

| Camera | Key | Description |
|--------|-----|-------------|
| Front | `observation.images.faceImg` | Third-person overhead view |
| Left wrist | `observation.images.leftImg` | Left arm wrist-mounted camera |
| Right wrist | `observation.images.rightImg` | Right arm wrist-mounted camera |

## Recording Frequency

All data is recorded at **20 Hz**.

## Quick Usage

```python
import pandas as pd
import numpy as np

# Load one episode
df = pd.read_parquet("real/execution_reasoning/put_blocks_to_color/data/chunk-000/episode_000000.parquet")

state = np.stack(df["observation.state"].tolist())  # (T, 56) for real, (T, 28) for sim
action = np.stack(df["action"].tolist())

# EE data (first 14 dims — same layout for real and sim)
ee_left = state[:, 0:7]    # xyz(3) + rpy(3) + gripper(1)
ee_right = state[:, 7:14]

# Joint data (real: index 14–51, sim: index 14–27)
left_joint_pos = state[:, 14:20]   # 6 joint positions
right_joint_pos = state[:, 33:39]  # real only (sim uses 21:27)
```

## Citation

If you find this dataset useful in your research, please consider citing:

```bibtex
@misc{sun2026maniparena,
      title={ManipArena: Comprehensive Real-world Evaluation of Reasoning-Oriented Generalist Robot Manipulation},
      author={Yu Sun and Meng Cao and Ping Yang and Rongtao Xu and Yunxiao Yan and Runze Xu and Liang Ma and Roy Gan and Andy Zhai and Qingxuan Chen and Zunnan Xu and Hao Wang and Jincheng Yu and Lucy Liang and Qian Wang and Ivan Laptev and Ian D Reid and Xiaodan Liang},
      year={2026},
      eprint={2603.28545},
      archivePrefix={arXiv},
      primaryClass={cs.RO},
      url={https://arxiv.org/abs/2603.28545},
}
```

## License

Apache License 2.0