README.md

---
pretty_name: 2D Navigation Sim datasets
license: other
license_name: mixed
task_categories:
  - robotics
  - reinforcement-learning
tags:
  - robot-navigation
  - gymnasium
  - hm3d
  - lidar
  - simulation
size_categories:
  - 10K<n<100K
viewer: false
extra_gated_heading: "Request access to the 2D Navigation Sim datasets"
extra_gated_description: "Access is reviewed manually. Three datasets are derived from HM3D: request them only if Matterport has granted you access to HM3D."
extra_gated_button_content: "Request access"
extra_gated_fields:
  Name: text
  Affiliation: text
  Country: country
  Intended use: text
  Datasets needed:
    type: select
    options:
      - "Isaac-Scene-Builder datasets only (isb-svg-v1, isb-grid-v1)"
      - "All, including the HM3D-derived ones (I have been granted access to HM3D by Matterport and accept its Terms of Use)"
  I will use the data for non-commercial research and cite the project: checkbox
---

# 2D Navigation Sim datasets

Pre-built datasets for [**hm3denv**](https://github.com/TrKimHieu/2D_Navigation_Sim), a physically
valid indoor robot-navigation simulator with a Gymnasium API. Each dataset holds 2D maps of
building storeys and navigation tasks (start, goal, geodesic distance, difficulty labels) for one
or more robots. Every start and goal was checked for collisions with the robot's real footprint
and for connectivity; an oracle agent solves 100 % of the tasks.

The 3D source scenes (HM3D `.glb` files, Isaac Sim scenes) are **not** included.

## Datasets

| Folder | Environment | Source | Maps | Scenes train / val / test | Robots | Tasks | Size |
|---|---|---|---|---|---|---|---|
| `isb-svg-v1` | `HM3D/Svg-v0` (continuous) | Isaac-Scene-Builder | 204 | 143 / 31 / 30 | 9 | 36 720 | 121 MB |
| `isb-grid-v1` | `HM3D/Grid-v0` (grid) | Isaac-Scene-Builder | 202 | 141 / 30 / 31 | `jetauto_pro` | 4 040 | 5 MB |
| `svg-v1` | `HM3D/Svg-v0` (continuous) | HM3D | 177 | 67 / 14 / 15 | 9 | 30 835 | 40 MB |
| `grid-jetauto-v1` | `HM3D/Grid-v0` (grid) | HM3D | 157 | 67 / 14 / 15 | `jetauto_pro` | 3 140 | 4 MB |
| `grid-s15-v1` | `HM3D/Grid-v0` (grid, 15 cm cells) | HM3D | 166 | 67 / 14 / 15 | `s15_h63` | 3 320 | 5 MB |

The 9 robots of the continuous datasets: `agilex_limo`, `clearpath_jackal`, `jetauto_pro`,
`kobuki`, `pal_tiago`, `turtlebot3_burger`, `turtlebot3_waffle_pi`, `turtlebot4`,
`turtlebot4_lite`. Splits are by scene: a building never appears in two splits.

## Usage

1. With a (free) Hugging Face account, request access with the form on this page and wait
   for the approval.
2. Install the simulator, log in once, and download datasets by name:

```bash
git clone https://github.com/TrKimHieu/2D_Navigation_Sim && cd 2D_Navigation_Sim
python -m venv .venv
source .venv/bin/activate        # Windows (PowerShell): .venv\Scripts\Activate.ps1
pip install ".[fast,hub]"        # the simulator + huggingface_hub (the `hf` command)
hf auth login                    # once per machine
hm3d download                    # list the datasets in this repository
hm3d download isb-svg-v1         # -> ~/.hm3denv/datasets/isb-svg-v1 (or $HM3D_HOME/datasets)
```

```python
import gymnasium as gym
import hm3denv

env = gym.make("HM3D/Svg-v0", dataset="isb-svg-v1", robot="turtlebot4", split="train")
obs, info = env.reset(seed=0)
```

Downloaded datasets are found by name and checked against the sha256 of every file in their
`manifest.json`. You can also download a folder with any Hugging Face tool and point
`HM3D_DATASETS` to its parent directory.

## Files

Each folder is one dataset (schema 2.0):

```
manifest.json            config, splits, per-robot statistics, sha256 of every file
maps/<class>/<map>.svg   continuous maps: polygons in metres (svg datasets)
grids/<map>.npz|.json    occupancy grids and their metadata (grid datasets)
robots/<robot>.json      the robot presets the tasks were built for
tasks/<robot>/<map>.json start / goal poses, geodesic and straight-line distance, labels
preview/                 PNG previews of the maps (not used by the simulator)
```

The full format is described in the
[simulator README](https://github.com/TrKimHieu/2D_Navigation_Sim#dataset-format).

## License

- **Isaac-Scene-Builder datasets** (`isb-svg-v1`, `isb-grid-v1`): built from scenes created by
  the author; released under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
- **HM3D-derived datasets** (`svg-v1`, `grid-jetauto-v1`, `grid-s15-v1`): derived from the
  [Habitat-Matterport 3D dataset](https://aihabitat.org/datasets/hm3d/). They are shared only
  with users who have been granted access to HM3D by Matterport, and their use is subject to
  the HM3D Terms of Use (non-commercial research).

The simulator code is MIT-licensed.

## Citation

```bibtex
@software{hm3denv,
  author  = {Tran, Kim Hieu},
  title   = {hm3denv: physically valid indoor robot-navigation environments from HM3D},
  year    = {2026},
  url     = {https://github.com/TrKimHieu/2D_Navigation_Sim},
  version = {0.8.0}
}
```

If you use the HM3D-derived datasets, please also cite HM3D:

```bibtex
@inproceedings{ramakrishnan2021hm3d,
  title     = {Habitat-Matterport 3D Dataset ({HM3D}): 1000 Large-scale 3D Environments for Embodied {AI}},
  author    = {Santhosh Kumar Ramakrishnan and Aaron Gokaslan and Erik Wijmans and Oleksandr Maksymets
               and Alexander Clegg and John M Turner and Eric Undersander and Wojciech Galuba
               and Andrew Westbury and Angel X Chang and Manolis Savva and Yili Zhao and Dhruv Batra},
  booktitle = {Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
  year      = {2021}
}
```