The Robotability Score

Enabling Harmonious Robot Navigation on Urban Streets

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@ CHI '25: ACM Conference on Human Factors in Computing Systems

What is The Robotability Score?

The Robotability Score (R) is a novel metric that quantifies how suitable urban environments are for autonomous robot navigation. Through expert interviews and surveys, we've developed a standardized framework for evaluating urban landscapes to reduce uncertainty in robot deployment while respecting established mobility patterns.

Streets with high Robotability are both more navigable for robots and less disruptive to pedestrians. We've constructed a proof-of-concept Robotability Score for New York City using a wealth of open datasets from NYC OpenData, and inferred pedestrian distributions from a dataset of 8 million dashcam images taken around the city in late 2023.

Interactive Map →

Explore the spatial distribution of Robotability Scores across New York City from our proof-of-concept deployment.

Key Features

Pedestrian Density: 11.1% Crowd Dynamics: 8.4% Pedestrian Flow: 8.1% Sidewalk Quality: 6.6% Street Width: 6.2% Density of Street Furniture: 5.9%

Our findings reveal that these factors collectively account for 48% of the total Robotability Score. Areas with highest R are 4.3 times more "robotable" than areas with lowest R.

Paper Citation

If you use our work in your research, please cite our paper:

@inproceedings{10.1145/3706598.3714009,
author = {Franchi, Matthew and Parreira, Maria Teresa and Bu, Fanjun and Ju, Wendy},
title = {The Robotability Score: Enabling Harmonious Robot Navigation on Urban Streets},
year = {2025},
isbn = {9798400713941},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3706598.3714009},
doi = {10.1145/3706598.3714009},
booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems},
articleno = {737},
numpages = {17},
series = {CHI '25}
}