---
license: mit
tags:
- robotics
- occupancy-grid
- motion-planning
- topological-traps
- floor-plans
- houseexpo
task_categories:
- image-segmentation
size_categories:
- 1K<n<10K
---

# Topological Traps Dataset

**TAU Algorithmic Robotics - Fall 2025/2026 - Daniel Simanovsky**

Pre-processed occupancy grids and Oracle viability labels derived from the
HouseExpo residential floor-plan dataset, used to train
[DanielDDDs/topological-traps](https://huggingface.co/DanielDDDs/topological-traps).

## Contents

| Path | Description | Size |
|---|---|---|
| `data/processed/` | 1,001 binary occupancy grids (512x512 px, .npy) | ~262 MB |
| `data/manifest.csv` | Train/val/test split (700/150/150), seed 42 | <1 MB |
| `data/labels/robot_20x15/` | Oracle viability labels, small robot | ~1 GB |
| `data/labels/robot_30x20/` | Oracle viability labels, default robot | ~1 GB |
| `data/labels/robot_40x25/` | Oracle viability labels, large robot | ~1 GB |
| `data/labels/robot_25x18/` | Oracle viability labels, unseen test robot | ~1 GB |

## Label format

Each label file is a (4, 512, 512) uint8 NumPy array.
Channel order: [North, South, East, West].
1 = viable (robot can escape), 0 = directional trap.

## Robot sizes

| Size (LxW px) | Diagonal (px) | Split |
|---|---|---|
| 20x15 | 25 | Train |
| 30x20 | 36 | Train |
| 40x25 | 47 | Train |
| 25x18 | 31 | Test only (unseen) |

## Oracle algorithm

1. Rotation-safe mask: erode free space with circular kernel of diameter sqrt(L^2+W^2)
2. Translation-safe masks: erode with oriented rectangular footprint per direction
3. Reverse BFS flood-fill: seed rotation+translation-safe pixels, propagate backwards

## Loading example

```python
import numpy as np

occ = np.load("data/processed/0041a20dcdfd5e0d1ca0752365a70634.npy")
# shape (512, 512), uint8, 1=free 0=wall

label = np.load("data/labels/robot_30x20/0041a20dcdfd5e0d1ca0752365a70634.npy")
# shape (4, 512, 512), uint8
north_viable = label[0]
```

## Source

1,000 maps from HouseExpo (Li et al., 2019, arXiv:1903.09845), rasterised to 512x512.

## Code

[github.com/danielsddd/topological-traps-project](https://github.com/danielsddd/topological-traps-project)