Gilbert Chang

2025

1. arXiv

   

   Foam: A Tool for Spherical Approximation of Robot Geometry

   Sai Coumar, Gilbert Chang, Nihar Kodkani, and Zachary Kingston

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   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.

   @misc{coumar2025foam,
     archiveprefix = {arXiv},
     author = {Coumar, Sai and Chang, Gilbert and Kodkani, Nihar and Kingston, Zachary},
     eprint = {2503.13704},
     primaryclass = {cs.RO},
     title = {Foam: A Tool for Spherical Approximation of Robot Geometry},
     year = {2025}
   }