---
license: other
task_categories:
- robotics
- reinforcement-learning
language:
- en
tags:
- robotics
- tactile-sensing
- visuotactile
- world-model
- manipulation
- open-x-tactile
pretty_name: ContactWorld
---

# ContactWorld

ContactWorld is a multimodal benchmark and dataset for learning predictive representations and world models for contact-rich robotic manipulation. This repository contains 12 simulated ContactWorld tasks converted to the FTP-1-compatible Open-X-Tactile (OXT) Zarr format.

- Project page: https://contact-world.github.io/
- Paper: https://arxiv.org/abs/2606.13877

## Tasks

| Task | Instruction |
|---|---|
| `disassembly_barbed_flat` | Pull the flat barbed plug out of the socket until it is fully disconnected. |
| `disassembly_barbed_spike` | Pull the spiked barbed plug out of the socket until it is fully disconnected. |
| `disassembly_lidded_loose` | Remove the loose lid from the container until the two parts are fully separated. |
| `exploration_search` | Explore the workspace through contact and locate the target object. |
| `exploration_sorting_dim` | Explore and sort the objects into their corresponding target regions under dim lighting. |
| `exploration_sorting_normal` | Explore and sort the objects into their corresponding target regions under normal lighting. |
| `insertion_peg` | Align the peg with the hole and insert it until it is fully seated. |
| `insertion_power` | Align the power plug with the socket and insert it until it is fully connected. |
| `insertion_usb` | Align the USB plug with the port and insert it until it is fully connected. |
| `screwing_bulb` | Pick up the light bulb and screw it into the socket until it is fully installed. |
| `screwing_nut` | Align the nut with the threaded bolt and screw it on until it is fully tightened. |
| `screwing_valve` | Turn the valve along its threaded axis until it reaches the target tightened state. |

## Robot and sensor

- Robot: Franka Panda
- End effector: parallel-jaw gripper
- Tactile sensor: `GelSightWedgeR1.5`
- Tactile functional-area ID: `0`
- Gripper joint index: `28`
- Dataset rate: 10 Hz
- Source quaternion order: `[w, x, y, z]`
- Exported wrist pose: `[x, y, z, rx, ry, rz]`, using a rotation vector

## Modalities

Each task Zarr contains front RGB, wrist RGB, end-effector pose, seven arm joints, one gripper joint, TacRGB, TacDepth, TacFF, per-frame language instruction, timestamps, and `meta/episode_ends`.

Important tactile arrays:

- `right_tactile_data_tacrgb`: `(T, 1, 320, 240, 3)`, `uint8`, type `image`
- `right_tactile_data_tacdepth`: `(T, 1, 320, 240, 1)`, `float32`, type `image`
- `right_tactile_data_tacff`: `(T, 1, 10, 14, 3)`, `float32`, type `matrix`

TacFF is copied from the source Zarr without additional scaling or normalization. It is not asserted to be calibrated in Newtons. See `supplementary_tactile_note.json`.

## Extraction

Each task is distributed as an independent ZIP archive:

```bash
unzip insertion_usb.zarr.zip
```

Then open it with Zarr:

```python
import zarr
root = zarr.open_group("insertion_usb.zarr", mode="r")
print(root["data"]["camera_main_rgb"].shape)
```

## Quality control

The processed dataset follows the three-step OXT-QC workflow:

1. metadata/Zarr structure precheck
2. 4D pose and trajectory visualization
3. RGB-tactile semantic review, performed manually when no VLM API is available