---
pretty_name: MAP-Bench
language:
- en
license: other
license_name: hm3d-derived-benchmark-terms
license_link: LICENSE.md
task_categories:
- robotics
size_categories:
- 10K<n<100K
viewer: false
tags:
- robotics
- navigation
- benchmark
- map-bench
- hm3d
---

<p align="center">
  <img src="assets/map.png" width="260" alt="MAP: Manipulation Anchor Pose" />
</p>
<h1 align="center">MAP-Bench</h1>
<p align="center">
  <a href="https://arxiv.org/abs/2609.39388">Paper</a> ·
  <a href="https://fysics-ai.github.io/uniwam.github.io/">Project</a> ·
  <a href="https://github.com/Fysics-AI/UniWAM">GitHub</a> ·
  <a href="https://huggingface.co/Fysics-AI/UniWAM">Checkpoints</a>
</p>

**MAP-Bench** evaluates instruction-conditioned navigation to a **Manipulation Anchor Pose**: the base position and heading from which a robot can begin the intended manipulation. Built in HM3D, it uses one forward RGB view and three distance levels: Short, Medium, and Long.

- **35,454 training trajectories** with RGB observations, navigation actions, instructions, target boxes, and MAP annotations.
- **15,000 evaluation episodes** with scene references, start poses, target MAPs, and instructions.
- **75,000 evaluation rollouts** and their results: 15,000 each for GR00T N1.7, π₀.₅, FastWAM, UniWAM-Base, and UniWAM-Scaled.

## Download

Run from your workspace directory to download the complete benchmark package (approximately **18.3 GB** before extraction):

```bash
python -m pip install -U huggingface_hub
hf download Fysics-AI/MAP-Bench --repo-type dataset --local-dir ./MAP-Bench
```

Training videos and evaluation rollouts are stored in compressed archives. Use the [GitHub download helper](https://github.com/Fysics-AI/UniWAM/blob/main/scripts/download_assets.py) with `--training --traces` to verify and extract them. Obtain [HM3D scene assets](https://aihabitat.org/datasets/hm3d/) separately for simulator evaluation.

## Usage

See GitHub for [benchmark setup and evaluation](https://github.com/Fysics-AI/UniWAM/blob/main/docs/EVALUATION.md), [navigation training](https://github.com/Fysics-AI/UniWAM/blob/main/training/NAVIGATION.md), and [results](https://github.com/Fysics-AI/UniWAM#map-bench-results).

HM3D-derived data are subject to the source dataset terms; see [LICENSE.md](LICENSE.md).