English

Foam: A Tool for Spherical Approximation of Robot Geometry

Robotics 2025-03-19 v1 Computational Geometry

Abstract

Many applications in robotics require primitive spherical geometry, especially in cases where efficient distance queries are necessary. Manual creation of spherical models is time-consuming and prone to errors. This paper presents Foam, a tool to generate spherical approximations of robot geometry from an input Universal Robot Description Format (URDF) file. Foam provides a robust preprocessing pipeline to handle mesh defects and a number of configuration parameters to control the level and approximation of the spherization, and generates an output URDF with collision geometry specified only by spheres. We demonstrate Foam on a number of standard robot models on common tasks, and demonstrate improved collision checking and distance query performance with only a minor loss in fidelity compared to the true collision geometry. We release our tool as an open source Python library and containerized command-line application to facilitate adoption across the robotics community.

Keywords

Cite

@article{arxiv.2503.13704,
  title  = {Foam: A Tool for Spherical Approximation of Robot Geometry},
  author = {Sai Coumar and Gilbert Chang and Nihar Kodkani and Zachary Kingston},
  journal= {arXiv preprint arXiv:2503.13704},
  year   = {2025}
}

Comments

6 pages, 6 figures, 2 tables. Submitted to IEEE/RSJ International Conference on Intelligent Robots and Systems 2025. Code available at https://github.com/CoMMALab/foam

R2 v1 2026-06-28T22:24:26.310Z