README.md

---
language:
- en
license: mit
license_link: LICENSE
pretty_name: omnislamproject
task_categories:
- robotics
- depth-estimation
- keypoint-detection
configs:
- config_name: default
  data_files:
  - split: stereo
    path: data/stereo-*
  - split: stereoinertial
    path: data/stereoinertial-*
  - split: vio
    path: data/vio-*
dataset_info:
  features:
  - name: image_left
    dtype: image
  - name: image_right
    dtype: image
  - name: timestamp
    dtype: float64
  - name: gyro
    list: float32
    length: 3
  - name: accel
    list: float32
    length: 3
  - name: sync_dt
    list: float32
    length: 2
  - name: position
    list: float32
    length: 3
  - name: orientation
    list: float32
    length: 4
  splits:
  - name: stereo
    num_bytes: 381314848
    num_examples: 100
  - name: stereoinertial
    num_bytes: 381134104
    num_examples: 100
  - name: vio
    num_bytes: 370323077
    num_examples: 100
  download_size: 1132892975
  dataset_size: 1132772029
---
# Omni Instrument SLAM Project Dataset

The Omni Instrument SLAM Project Dataset is a compact robotics dataset designed for evaluating stereo, visual-inertial, and visual-inertial odometry (VIO) pipelines.

It provides:
- [x] Stereo Image Pairs
- [x] Inertial measurements (IMU)
- [x] Ground-truth 6 DoF pose (for VIO)
- [x] Raw ROS 1 and ROS 2 recordings

## Overview

The dataset is structured into three splits:

| Split | Description |
| --- | --- |
| `stereo` | Stereo-only (IMU stationary) |
| `stereoinertial` | Stereo + IMU |
| `vio` | Stereo + IMU + ground-truth pose |

All splits share the same schema, enabling consistent downstream pipelines.

## Data Collection Protocol

AprilTag grid settings (used for both **Stereo** and **Stereo-Inertial** calibration sequences):

| Setting | Value |
| --- | --- |
| Tag size | 20 mm |
| Tag spacing | 6 mm |
| Tag family/dictionary | `tag36h11` (6x6) |

1. Stereo (Calibration - Static Sensor)
   - Setup: robot stationary, camera + IMU fixed, AprilTag grid moves
   - Used for: stereo calibration (intrinsics/extrinsics)

   ![Stereo calibration preview](assets/stereo.gif)

2. Stereo-Inertial (Calibration - Moving Sensor)
   - Setup: robot moves, camera + IMU move together, AprilTag grid stationary
   - Used for: camera-IMU extrinsics + sync checks

   ![Stereo-inertial calibration preview](assets/stereo-imu.gif)

3. VIO (Operational SLAM Sequence)
   - Setup: robot moves in a normal environment (no calibration targets)
   - Logged: stereo images, IMU, ground-truth odometry
   - Used for: VIO/SLAM evaluation

   ![VIO sequence preview](assets/vio.gif)

## Data Format

Each example follows the same top-level schema. Some fields are split-dependent:

- `stereo`: images + `timestamp` (IMU is stationary; pose not provided)
- `stereoinertial`: adds IMU (`gyro`, `accel`) and time offsets (`sync_dt`)
- `vio`: adds ground-truth pose (`position`, `orientation`)

Example record:
```json
{
  "image_left": Image,
  "image_right": Image,
  "timestamp": float,

  "gyro": [wx, wy, wz],
  "accel": [ax, ay, az],

  "sync_dt": [dt_right, dt_imu],

  "position": [x, y, z],
  "orientation": [qx, qy, qz, qw]
}
```

Notes:
- `gyro` is in rad/s and `accel` is in m/s^2.
- `sync_dt = [dt_right, dt_imu]` are time offsets (in seconds) relative to `timestamp` (left image):
  - `dt_right = abs(t_right - t_left)`
  - `dt_imu = abs(t_imu - t_left)`

### Sampling Methodology

Each split contains 100 randomly sampled, synchronized frames:
- Uniform sampling across the trajectory
- Start/end trimmed to remove initialization artifacts

Synchronization constraints:
- abs(t_left - t_right) <= 5 ms
- abs(t_left - t_imu) <= 5 ms
- abs(t_left - t_odom) <= 5 ms (VIO only)

### Missing Data Handling

For splits without ground truth (stereo, stereoinertial):

```text
position    = [inf, inf, inf]
orientation = [inf, inf, inf, inf]
```

### ROS Topics

Recordings:
- ROS 1 bags: [stereo](ros1/omni_stereo_20260425_215907Z.bag), [stereointertial](ros1/omni_stereointertial_20260425_220304Z.bag)
- ROS 2 MCAP: [vio](ros2/omni_vio_20260425_220737Z_with_gt/omni_vio_20260425_220737Z_with_gt_0.mcap)

#### ROS 1 (Calibration)
```text
/stereo/left/color/image_raw
/stereo/right/color/image_raw
/imu/data
```

#### ROS 2 (VIO)
```text
/stereo/left/color/image_raw
/stereo/right/color/image_raw
/imu/data
/ground_truth/odom
/tf
```

## Example Usage

```python
from datasets import load_dataset
import numpy as np

ds = load_dataset("OmniInstrument/SLAM_project", split="vio")
sample = ds[0]

img_l = sample["image_left"]
img_r = sample["image_right"]

gyro = sample["gyro"]
accel = sample["accel"]

pos = sample["position"]
quat = sample["orientation"]

if not np.isinf(np.asarray(pos)).any():
    print("Ground truth available")
```

## License
This software and dataset are released under the [MIT License](LICENSE).