MachEmbodied / ScaleNav

ScaleNav 
 Scalable Internet Video Pretraining for Language-Conditioned Local Navigation 
 Yihui Yang 1 ·
 Yuanhong Yu 1 ·
 Jiawei Wang 1 ·
 Zhongrui Yu 2 ·
 Jia Shi 2 
 Kun Zhan 2 ·
 Ruizhen Hu 3 ·
 Xiaowei Zhou 1 ·
 Yu Liu 2 ·
 Sida Peng 1 
 1  Zhejiang University   2  Li Auto Inc.   3  Shenzhen University
> **TL;DR:** ScaleNav learns navigation priors from Internet videos through **action-free pretraining**, then transfers them to **language-conditioned local navigation**.
 Installation ·
 Checkpoints ·
 Data ·
 Quick test ·
 Evaluation ·
 Training ·
 Real robot 
## Installation
Use Linux and an NVIDIA GPU with BF16 support. We recommend **24 GB GPU memory**
and **64 GB system RAM** for inference and evaluation.
Follow the installation guide to set up the `scalenav`
environment, Habitat-GS and the scene converter.
## Checkpoints
| Model | Download | Size |
| --- | --- | ---: |
| ScaleNav | Hugging Face | 10.02 GB |
| Wan VAE, text encoder and tokenizer | Wan2.2-TI2V-5B | 14.20 GB |
Follow the checkpoint download steps to download
both models and set `CHECKPOINT` and `BASE_MODEL`.
## Data
Select a dataset below for its complete download and preparation instructions,
including our annotations and the required upstream assets.
| Dataset | Purpose | Contents | Network download | Disk usage after preparation |
| --- | --- | --- | ---: | ---: |
| Habitat-GS-LN test subset | Preview navigation and visualizations | 16 tasks / 13 scenes | 991.32 MB | 2.96 GB |
| Full Habitat-GS-LN evaluation | Report Habitat-GS-LN SR/SPL | 157 tasks / 45 scenes | 3.17 GB | 10.36 GB |
| Short-Horizon OVON test subset | Preview navigation on HM3D | 7 tasks / 7 scenes | 642.85 MB | 642.90 MB |
| Full Short-Horizon OVON evaluation | Report Short-Horizon OVON SR/SPL | 524 tasks / 36 scenes | 5.84 GB | 3.67 GB |
| Small training subset (for preview) | Check the training pipeline | 17 Internet segments / 4 simulated episodes | 55.60 MB | 239.54 MB |
| Full training data | Pretrain and fine-tune ScaleNav | 18,249 Internet segments / 2,600 simulated episodes, including validation | 36.10 GB | 153.04 GB |
Network download includes all sources. Disk usage includes prepared assets and
retained downloads after cleanup; full OVON needs **9.34 GB** before archive cleanup.
Model weights, environments, training caches and run outputs are separate.
See data details or
ScaleNav Data.
## Quick test
After installation and checkpoint downloads,
run the **Habitat-GS-LN test subset** to view navigation videos and trajectories.
It contains **16 tasks in 13 scenes**, requiring **991.32 MB** of network
downloads and **2.96 GB** on disk after preparation.
### Prepare the test subset
Request InteriorGS access
and accept its terms,
then prepare the data:
 [code] 
### Run navigation
Run the prepared test subset with visualization enabled:
 [code] 
Open `outputs/evaluation/test_subset/gallery/index.html` to view the videos and
trajectories. Metrics are saved in `outputs/evaluation/test_subset/summary