This project provides sim2val
--a Python package with utilities for validation using simulated data. For
more information, please see the paper.
The python package can be built with either:
# Using uv
uv run python -m build
# Using pip
python -m build .
And if using pip
, installed with:
pip install .
To get started with sim2val
, you can run the example notebooks--for example:
jupyter notebook notebooks/simple_run.ipynb
# or
uv run python -m jupyter notebook notebooks/simple_run.ipynb
Unit tests are found in the tests
directory and can be run with:
# Using uv
uv run --all-extras pytest
# Using pip
pytest
If you use this code, please cite the following paper:
@inproceedings{luo2025_sim2val,
title = {Sim2Val: Leveraging Correlation Across Test Platforms for Variance-Reduced Metric Estimation},
author = {Rachel Luo and Heng Yang and Michael Watson and Apoorva Sharma and Sushant Veer and Edward Schmerling and Marco Pavone},
booktitle = {Proceedings of the Conference on Robot Learning (CoRL)},
year = {2025},
}